Simultaneous noninvasive ultrasensitive detection of prostate specific antigen and lncRNA PCA3 using multiplexed dual optical microfibers with strong plasmonic nanointerfaces.

Low accuracy of diagnosing prostate cancer (PCa) was easily caused by only assaying single prostate specific antigen (PSA) biomarker. Although conventional reported methods for simultaneous detection of two specific PCa biomarkers could improve the diagnostic efficiency and accuracy, low detection sensitivity restrained their use in extreme early-stage PCa clinical assay applications. In order to overcome above drawbacks, this paper herein proposed a multiplexed dual optical microfibers separately functionalized with gold nanorods (GNRs) and Au nanobipyramids (Au NBPs) nanointerfaces with strong localized surface plasmon resonance (LSPR) effects. The sensors could simultaneously detect PSA protein biomarker and long noncoding RNA prostate cancer antigen 3 (lncRNA PCA3) with ultrahigh sensitivity and remarkable specificity. Consequently, the proposed dual optical microfibers multiplexed biosensors could detect the PSA protein and lncRNA PCA3 with ultra-low limit-of-detections (LODs) of 3.97 × 10-15 mol/L and 1.56 × 10-14 mol/L in pure phosphorus buffer solution (PBS), respectively, in which the obtained LODs were three orders of magnitude lower than existed state-of-the-art PCa assay technologies. Additionally, the sensors could discriminate target components from complicated physiological environment, that showing noticeable biosensing specificity of the sensors. With good performances of the sensors, they could successfully assay PSA and lncRNA PCA3 in undiluted human serum and urine simultaneously, respectively. Consequently, our proposed multiplexed sensors could real-time high-sensitivity simultaneously detect complicated human samples, that providing a novel valuable approach for the high-accurate diagnosis of early-stage PCa individuals.

Distribution characteristics and risk assessment of fluoride in surface water of urban typical rivers.

Recent research on fluoride in water primarily focuses on groundwater; however, the potential environmental risks of fluoride in urban rivers should not be overlooked. In 2023, this study collected 135 surface water samples from the Ershibu River in Hefei, China, during various flood periods. Through descriptive statistical analysis, correlation analysis, principal component analysis-multiple linear regression (PCA-MLR) modeling, hazard quotient (HQ) assessment, and Monte Carlo simulation analysis, the spatial and temporal distribution, potential sources, and health risks of fluoride were investigated. The results showed that fluoride concentrations in the Ershibu River ranged from 0 to 1.38 mg/L. According to the PCA-MLR calculations, industrial pollution (73.92 %) was identified as the main source, followed by hydrogeochemical evolution (16.10 %) and agricultural activities (9.98 %). The HQ analysis revealed that the average exceedance rates of HQ for the five exposed populations were as follows: infants (64.45 %) > young children (2.22 %) = adults (2.22 %) > children (0) = teenagers (0). Therefore, relevant authorities should improve defluoridation facilities to reduce fluoride levels in industrial and agricultural wastewater and implement measures to protect public health. Future research should investigate the migration processes and toxicity mechanisms of fluoride more thoroughly.

Evaluation of Proximate Composition, Cooking Quality, and Texture Profile Analysis in Himalayan Landraces of Black Gram (Vigna mungo).

The black gram is a traditional pulse crop and is a source of different nutritional components. Due to the scientific community's preference for yield and its components, the area of nutritional composition remains unexplored. Therefore, the evaluation of various quality traits such as proximate composition, cooking quality, texture profile, and association between them is keen important for the identification of the traits influencing the selection of the genotypes. This research aimed at the evaluation of the 25 black gram genotypes for their proximate composition, the effect of different cooking methods (conventional and microwave) on cooking quality parameters, and texture profile analysis. The genotypes were screened on 17 parameters, mean and replicated value of each variable were subjected to statistical analysis. The results for proximate composition showed the range from 11.2-11.7%, 24.24-28.22%, 1.25-1.85%, 3.10-4.45%, 5.35-6.60%, 60.23-64.86% and 368.35-372.75 Kcal/100 g for moisture, protein, fat, dietary fiber, ash, utilizable carbohydrate, and gross energy respectively. Cooking time ranged from 33 to 55.5 min (traditional) to 29.5-48.5 min (microwave), L: B ratio from 1.35 to 1.85, WUR from 1.85 to 2.60, and GSL from 0.25 to 11.30%. TPA's cohesiveness, gumminess, and chewiness ranged from 0.19 to 1.44 N, 0.14-1.30 N, 0.58-3.67 N, 1.14-10.81 N, and 0.58-5.29; 1.16-10.50 N in traditional and microwave cooking. Chewiness, gumminess, protein, ash, and cooking time were positively correlated. The first seven PCs have ≥ 1 eigenvalues, accounting for 23.30, 18.00, 13.50, 9.50, 7.40, 6.70%, and 6.40% of total variability. Mandi-2, Kinnour-1, Kirmour-1, Kangra-2, Bilaspur-1, Kangra-3, Kullu-1, Kullu-4, Chamba-3, and Chamba-7 to PCs 1-2 contributed the most to diversity, indicating good selection for subsequent upgrading initiatives.

Multivariate Data Analysis Assisted Mining of Nutri-rich Genotypes from North Eastern Himalayan Germplasm Collection of Perilla (Perilla frutescens L.).

Understanding the nutritional diversity in Perilla (Perilla frutescens L.) is essential for selecting and developing superior varieties with enhanced nutritional profiles in the North Eastern Himalayan (NEH) region of India. In this study, we assessed the nutritional composition of 45 diverse perilla germplasm collected from five NEH states using standard protocols and advanced analytical techniques. Significant variability was observed in moisture (0.39-11.67%), ash (2.59-7.13%), oil (28.65-74.20%), protein (11.05-23.15%), total soluble sugars (0.34-3.67%), starch (0.01-0.55%), phenols (0.03-0.87%), ferric reducing antioxidant power (0.45-1.36%), palmitic acid (7.06-10.75%), stearic acid (1.96-2.29%), oleic acid (8.11-13.31%), linoleic acid (15.18-22.74%), and linolenic acid (55.47-67.07%). Similarly, significant variability in mineral content (ppm) was also observed for aluminium, calcium, cobalt, chromium, copper, iron, potassium, magnesium, manganese, molybdenum, sodium, nickel, phosphorus, and zinc. Multivariate analyses, including hierarchical clustering analysis (HCA) and principal component analysis (PCA), revealed the enriched nutritional diversity within the germplasm. Correlation analysis indicated significant positive and negative relationships between nutritional parameters, indicating potential biochemical and metabolic interactions present in the perilla seeds. TOPSIS-based ranking identified promising genotypes for functional foods, pharmaceuticals, and nutritional applications. This study provides a first in-depth report of the nutritional composition and diversity of perilla germplasm in the NEH region, thus aiding in the identification of superior varieties for food and nutritional diversification and security.

Utilizing Liquid-liquid phase separation-related lncRNAs to predict the prognosis and treatment response of PCa.

BACKGROUND: Studies have indicated a close association between genes linked to liquid-liquid phase separation (LLPS) and the progression of prostate cancer (PCa). However, the interplay among long non-coding RNAs (lncRNAs) linked to LLPS in PCa remains elusive. Therefore, we constructed a prediction model based on LLPS-related LncRNA in PCa to explore its relationship with the prognosis and drug treatment of PCa. METHODS: We obtained clinical and sequencing data from TCGA and LLPS genes from the Phase Separation Protein Database. By analyzing the differential expression of LLPS-related genes and lncRNAs in prostate cancer, and using Poisson correlation, we identified LLPS-related lncRNAs. Prognostic LLPS-lncRNAs were found through prognostic correlation analysis and included in a Cox model to compute regression coefficients. Patients were scored and divided into high- and low-risk groups. Independent prognostic factors were integrated into a prognostic nomogram with risk and Gleason scores. We also conducted drug sensitivity analyses, GSEA, and validated the impact of key lncRNAs through functional experiments. RESULTS: Our study identified five LLPS-associated lncRNAs that are of prognostic importance. And found notable disparities in biochemical recurrence rates and survival outcomes between these risk groups, with the low-risk cohort exhibiting superior prognostic indicators. Moreover, our prediction nomogram demonstrated robust predictive accuracy and significant clinical utility. Furthermore, our model exhibited promising capabilities in forecasting patient sensitivity to various conventional therapeutic drugs, thereby highlighting its potential in personalized treatment strategies. GSEA showed that these lncRNAs may influence PCa prognosis and sensitivity to therapeutic agents by affecting pathways such as cell cycle. Knockdown of AC009812.4 could inhibit the ability of PCa cells to proliferate, migrate and invade, and compare to paracancerous tissue, AC009812.4 in PCa tissue has significantly higher expression. CONCLUSION: Our research uncovers the prognostic significance of lncRNAs associated with LLPS in PCa and established a model exhibiting excellent predictive accuracy for prognosis. Those lncRNAs may influence progress of PCa as well as sensitivity to therapy drugs through pathways such as cell cycle.

Energy efficiency identification and surface roughness prediction using cutting force signal for computer numerical controlled machine systems.

The energy efficiency identification of machining process plays an indispensable part in achieving energy-efficient manufacturing and improving energy utilization as well as productivity and surface quality. However, there is a great difficulty to track energy efficiency in real-time based on one kind of traditional power signal. Because energy consumption is affected by many factors such as machine tool current performance, tool wear conditions and cutting parameters selection. This paper puts forward an energy efficiency recognition method as well as surface roughness prediction model based on the cutting force signals. The CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) algorithm is employed to decompose the cutting force signal into multiple IMF (intrinsic mode function) components; and characterization of energy efficiency of machining process is recognized through proportion of components based on PCA-Fast ICA algorithm. Then, a surface roughness prediction model is proposed using support vector regression (SVR) based on specific cutting energy consumption (SCEC). The orthogonal test is designed considering spindle speed, feed rate, depth of cutting and width of cutting in 3 levels to obtain the influence degree of cutting parameters on cutting force, specific energy consumption, and the surface roughness. The energy efficiency of 27 group experiments is classified into high, medium and low levels according to energy efficiency value. Finally, using the data of orthogonal test, energy efficiency state was identified. The result show that time-frequency of cutting force signals for high, medium and low energy efficiency could be extracted, and the average absolute error of surface roughness predict is 0.058. That illustrated that the proposed method could meet the industry requirement for energy efficiency monitoring and surface roughness prediction to achieve sustainable manufacturing.

Evaluating the Prevalence and Clinical Significance of Fetal Posterior Cerebral Artery Variants via Magnetic Resonance Imaging: Insights From a Tertiary Healthcare Facility in Tamil Nadu.

Introduction The prevalence and clinical significance of fetal posterior cerebral artery (FPCA) variants are studied using magnetic resonance imaging (MRI) at Saveetha Medical College. This research focuses on the fetal origin of the posterior cerebral artery (PCA), a condition where the posterior communicating artery (PComA) is larger than the P1 segment of the PCA, affecting cerebral hemodynamics and associated with various cerebrovascular pathologies. Materials and methods This retrospective analysis employed MRI records from the Department of Radio Diagnosis at Saveetha Medical College, conducted between January 2013 and December 2023. The study included patients undergoing MRI for various neurological indications, with specific imaging protocols including T1- and T2-weighted sequences, diffusion-weighted imaging, and magnetic resonance angiography (MRA). Results The study confirmed a prevalence rate of FPCA variants within the expected range of 20%-30%. MRI findings were systematically analyzed by experienced radiologists to assess the presence and characteristics of FPCA variants. The relationship between these variants and clinical symptoms was explored, revealing significant correlations that emphasize the variants' impact on patient outcomes, particularly in the context of cerebrovascular events. Conclusion The study underlines the importance of recognizing FPCA variants due to their significant implications in neurovascular health and cerebrovascular accident (CVA) outcomes. These variants alter cerebral hemodynamics and can complicate neurosurgical and diagnostic procedures. Therefore, personalized treatment and management strategies are crucial for optimizing patient care.

Mathematical optimization of multilinear and artificial neural network regressions for mineral composition of different tea types infusions.

The objective of this study was to investigate the change in mineral composition depending on tea variety, tea concentration, and steeping time. Four different tea varieties, black Ceylon (BC), black Turkish (BT), green Ceylon (GC), and green Turkish (GT), were used to produce teas at concentrations of 1, 2, and 3%, respectively. These teas were produced using 7 different steeping times: 2, 5, 10, 20, 30, 45, and 60 min. It was also aimed to optimize the regression equations utilizing these factors to identify parameters conducive to maximizing Zn, K, Cu, Mg, Ca, Na, and Fe levels; minimizing Al content, and maintaining Mn level at 5.3 mg/L. The optimal conditions for achieving a Mn content of 5.3 mg/L in black Turkish tea entailed steeping at a concentration of 1.94% for 11.4 min. Variations in K and Mg levels across teas were inconsistent with those observed for other minerals, whereas variations in Al, Cu, Fe, Mn, Na, and Zn levels exhibited a close relationship. Overall, mineral levels in tea can be predicted through regression analysis, and by mathematically optimizing the resultant equations, the requisite conditions for tea production can be determined to achieve maximum, minimum, or target mineral values.

Fabrication of Aluminum Foil Integrated Pegylated Gold Nanoparticle Surface-Enhanced Raman Scattering Substrate for the Detection and Classification of Uropathogenic Bacteria.

Rapid detection and classification of pathogenic microbes for food hygiene, healthcare, environmental contamination, and chemical and biological exposures remain a major challenge due to nonavailability of fast and accurate detection methods. The delay in clinical diagnosis of the most frequent bacterial infections, particularly urinary tract infections (UTIs), which affect about half of the population at least once in their lifetime, can be fatal if not detected and treated appropriately. In this work, we have fabricated aluminum (Al) foil integrated pegylated gold nanoparticles (AuNPs) as a potential surface-enhanced Raman scattering (SERS) substrate, which is used for the detection and classification of uropathogens, namely, E. coli, S. aureus, and P. aeruginosa directly from the culture without any pretreatment. The substrate is first drop cast with bacterial pellets and then pegylated AuNPs, and the interaction of two on Al foil base gives identifiable characteristic Raman peaks with good reproducibility. With the use of chemometric methods such as principal component analysis (PCA), the Al foil-based SERS substrate offers a quick, effective detection and classification of three strains of UTI bacteria with the least bacterial concentration (105 cells mL-1) necessary for clinical diagnosis. In addition, this substrate was able to detect E. coli positive clinical samples by giving SERS fingerprint information directly from centrifuged urine samples within minutes. The stability of pegylated AuNPs provides for its application at the point of care with rapid and easy detection of uropathogens as well as the possibility of advancement in healthcare applications.

Mapping protein conformational landscapes from crystallographic drug fragment screens.

Proteins are dynamic macromolecules. Knowledge of a protein's thermally accessible conformations is critical to determining important transitions and designing therapeutics. Accessible conformations are highly constrained by a protein's structure such that concerted structural changes due to external perturbations likely track intrinsic conformational transitions. These transitions can be thought of as paths through a conformational landscape. Crystallographic drug fragment screens are high-throughput perturbation experiments, in which thousands of crystals of a drug target are soaked with small-molecule drug precursors (fragments) and examined for fragment binding, mapping potential drug binding sites on the target protein. Here, we describe an open-source Python package, COLAV (COnformational LAndscape Visualization), to infer conformational landscapes from such large-scale crystallographic perturbation studies. We apply COLAV to drug fragment screens of two medically important systems: protein tyrosine phosphatase 1B (PTP-1B), which regulates insulin signaling, and the SARS CoV-2 Main Protease (MPro). With enough fragment-bound structures, we find that such drug screens also enable detailed mapping of proteins' conformational landscapes.

Reversed phase HPLC with UHPLC benefits for the determination of tocochromanols in the seeds of edible fruits in the Rosaceae family.

Rosaceae family includes several edible fruit species processed in vast quantities and generates large amounts of seeds valuable in tocopherols. In the present study, the composition of tocochromanols in the seeds of 141 samples was determined by reversed phase high-performance liquid chromatography (RPLC) with diode array detector (DAD), fluorescence detector (FLD) and confirmed by mass detector (MS). The thirteen species belonging to the Rosaceae family were classified by multivariate statistical analysis, hierarchical cluster analysis (HCA) and principal component analysis (PCA) into two groups based on tocochromanols content. Group 'A' includes pears (Pyrus communis), sweet cherry (Prunus avium), sour cherry (Prunus cerasus), apricots (Prunus armeniaca), hexaploid plums (Prunus domestica), diploid plums (Prunus cerasifera), raspberry (Rubus idaeus), and rose hip (Rosa rugosa); while group 'B' quince (Cydonia oblonga), Japanese quince (Chaenomeles japonica), strawberry (Fragaria × ananassa), dessert apples (Malus domestica), and crab apples (Malus spp.). Two rapid (6-7 min) and low pressure (7.2-8.1 MPa) separation methods were developed and validated using two core-shell columns (i) C18 and (ii) F5. The F5 achieved a separation of ß and γ isomers while the C18 column did not.

Green plastics: Direct production from grocery wastes to bioplastics and structural characterization by using synchrotron FTIR.

Lignocellulosic bioplastics were produced using four different green wastes: hemp, parsley stem, pineapple leaves and walnut shell. Two different solutions were used to dissolve the green wastes: trifluoroacetic acid (TFA) and pure water. The changes in their natural structures and the solvent effect during the regeneration in biofilm formation were investigated by using Synchrotron FTIR Microspectroscopy (SR-µFTIR). The presence of cellulose, hemicellulose and lignin components in the water-based biofilms was confirmed. After dissolving in TFA, the spectra demonstrated some additional bands especially in the hemicellulose region. This is due to the hydrolysis of ester bonds and conversion to carboxylic acids. Principal component analysis showed grouping due to different solvents and polymer addition. Hemp-PVA (Polyvinyl Alcohol) composite biofilms were obtained by adding polyvinyl alcohol to the hemp solution to give extra strength to the hemp biofilms. It has been shown that water-based hemp-PVA biofilms do not cause any significant spectral changes, comparing with pure hemp and PVA spectra. However, after dissolving in TFA, unlike water-based biofilms, it appears that TFA molecules are retained by PVA through hydrogen bonds of TFA's carboxylic acid and hydroxyl groups and distinct spectral regions belong to TFA bands are clearly identified.

Insights on the comparative affinity of ribonucleic acids with plant-based beta carboline alkaloid, harmine: Spectroscopic, calorimetric and computational evaluation.

Small molecules as ligands target multifunctional ribonucleic acids (RNA) for therapeutic engagement. This study explores how the anticancer DNA intercalator harmine interacts various motifs of RNAs, including the single-stranded A-form poly (rA), the clover leaf tRNAphe, and the double-stranded A-form poly (rC)-poly (rG). Harmine showed the affinity to the polynucleotides in the order, poly (rA) > tRNAphe > poly (rC)·poly (rG). While no induced circular dichroism change was detected with poly (rC)poly (rG), significant structural alterations of poly (rA) followed by tRNAphe and occurrence of concurrent initiation of optical activity in the attached achiral molecule of alkaloid was reported. At 25 °C, the affinity further showed exothermic and entropy-driven binding. The interaction also highlighted heat capacity (ΔC o p ) and Gibbs energy contribution from the hydrophobic transfer (ΔG hyd) of binding with harmine. Molecular docking calculations indicated that harmine exhibits higher affinity for poly (rA) compared to tRNAphe and poly (rC)·poly (rG). Subsequent molecular dynamics simulations were conducted to investigate the binding mode and stability of harmine with poly(A), tRNAphe, and poly (rC)·poly (rG). The results revealed that harmine adopts a partial intercalative binding with poly (rA) and tRNAphe, characterized by pronounced stacking forces and stronger binding free energy observed with poly (rA), while a comparatively weaker binding free energy was observed with tRNAphe. In contrast, the stacking forces with poly (rC)·poly (rG) were comparatively less pronounced and adopts a groove binding mode. It was also supported by ferrocyanide quenching analysis. All these findings univocally provide detailed insight into the binding specificity of harmine, to single stranded poly (rA) over other RNA motifs, probably suggesting a self-structure formation in poly (rA) with harmine and its potential as a lead compound for RNA based drug targeting.

Risk factors for secondary bladder cancer following prostate cancer radiotherapy.

This review investigates the complex landscape of secondary bladder cancer (SBC) after radiotherapy for prostate cancer (PCa). External beam radiotherapy (EBRT) poses an increased risk for SBC, while brachytherapy seems to be associated with smaller increased risks for SBC due to its targeted radiation delivery, sparing the surrounding bladder tissue. Secondary cancers in the bladder are the most frequently diagnosed secondary cancers in the PCa patient population treated with radiotherapy. Patient-related factors are pivotal, with age emerging as a dual-edged factor. While advanced age is a recognized risk for bladder cancer, younger PCa patients exhibit higher susceptibility to radiation-induced cancers. Smoking, a well-established bladder cancer risk factor, increases this vulnerability. Studies highlight the synergistic effect of smoking and radiation exposure, amplifying the likelihood of genetic mutations and SBC. The latency period of SBC, which spans years to decades, remains a critical aspect. There is a strong dose-response relationship between radiation exposure and SBC risk, with higher doses consistently being associated with a higher SBC risk. While specific models for therapeutic radiation-induced SBC are lacking, insights from related studies, like the Atomic Bomb survivor research, emphasize the bladder's sensitivity to radiation-induced cancer. Chemotherapy in combination with radiotherapy, although infrequently used in PCa, emerges as a potential risk for bladder cancer. Bladder cancer's complex epidemiology, encompassing risk factors, treatment modalities, and cancer types, provides a comprehensive backdrop. As research refines understanding, we hope that this review contributes to guide clinicians, inform patient care, and shape preventive strategies on SBC.

Racial, ethnic, and socioeconomic disparities in rates of stage IV prostate cancer after USPSTF category "D" recommendation against prostate-specific antigen screening: a retrospective cohort study.

Background: In 2012 the United States Preventative Services Task Force (USPSTF) changed its prostate-specific antigen (PSA) screening recommendation to a category "D". The purpose of this study is to examine racial, ethnic, and socioeconomic differences in risk of presentation with metastatic prostate cancer (mPCa) at time of diagnosis before and after the 2012 USPSTF category "D" recommendation. Methods: This is a population-based cohort study. We identified patients with mPCa at diagnosis within the National Cancer Database from 2004-2017. Logistic regression models were used to examine associations of mPCa with age, race, ethnicity, geographic location, education level, income, and insurance status. Linear regression models assuming underlying binomial distribution were fitted to annual percentage of mPCa at diagnosis for years 2012-2017 to evaluate the post category "D" recommendation era. Results: From 2004 to 2017, 88,987 patients presented with mPCa. A higher percentage of mPCa was noted post-USPSTF category "D" recommendation, with a disproportionately greater increase observed among Hispanics and non-Hispanic Blacks [Δslope/year: Hispanics (0.0092), non-Hispanic Blacks (0.0073) and non-Hispanic Whites (0.0070)]. Insurance status impacts race/ethnicity differently: uninsured Hispanics were 3.66 times more likely to present with mPCa than insured Hispanics, while uninsured non-Hispanic Blacks were 2.62 times more likely to present with mPCa than insured non-Hispanic Blacks. Household income appears to be associated with differences in mPCa, particularly among non-Hispanic Blacks. Those earning <$30,000 were more likely to present with mPCa compared to higher income brackets. Conclusions: Since the USPSTF grade "D" recommendation against PSA screening, the percentage of mPCa at diagnosis has increased, with a higher rate of increase among Hispanic and non-Hispanic Blacks compared to non-Hispanic Whites.

METTL14 inhibits the proliferation, migration and invasion of prostate cancer cells by increasing m6A methylation of CDK4.

Background: Methyltransferase-like (METTL) plays an important role in various biological processes, but its role in prostate cancer (PCa) is still unclear. This study aimed to explore the mechanism by which methyltransferase-like 14 (METTL14) inhibits the physiological activity of PCa cells by increasing the N6-methyladenosine (m6A) modification of cyclin-dependent kinase 4 (CDK4). Methods: Clinical samples were collected for bioinformatics analysis. A PCa mouse model was constructed. Cell counting kit-8 (CCK-8), flow cytometry, colony formation assays, scratch assays, Transwell assays, real-time quantitative polymerase chain reaction (RT-qPCR), immunofluorescence and western blotting were used to detect the corresponding indicators. Results: METTL14 was found to be beneficial to inhibit the proliferation, invasion, and migration of PCa cells. When the m6A RNA increased, the half-life of CDK4 mRNA decreased after oe-METTL14 (overexpression of METTL14). Overexpression of CDK4 reversed the effect of oe-METTL14. Coimmunoprecipitation experiments revealed there were interactions between CDK4 and forkhead box M1 (FOXM1). Transfection of si-CDK4 was similar to transfection of oe-METTL14. After transfection with oe-FOXM1, the invasion and migration ability of cells increased, and cell apoptosis decreased. After transfection with si-FOXM1 alone, autophagy related 7 (ATG7) expression was significantly downregulated, and autophagy levels were reduced. The overexpression of ATG7 reversed the effect of si-FOXM1. The tumor volume and weight of the oe-METTL14 group mice were significantly reduced, and tumor proliferation was decreased in comparison to untreated tumor-bearing mice. Conclusions: METTL14 inhibits the invasion and migration of PCa cells and induces cell apoptosis by inhibiting CDK4 stability and FOXM1/ATG7-mediated autophagy.

A review of tanshinone compounds in prostate cancer treatment.

Prostate cancer (PCa) is one of the most common malignant epithelial tumors in men worldwide. PCa patients are initially sensitive to chemotherapy, but patients in the advanced stages of PCa eventually develop resistance, leaving them with limited therapeutic options. Therefore, it is very important to screen new drugs for treating PCa. Salvia miltiorrhiza is a common Chinese herbal medicine used in some Asian countries. It has many functions and is widely used to treat a variety of diseases, including heart diseases and cancers. For the past few years, research has shown that liposoluble constituents of tanshinones (TANs), including cryptotanshinone, TAN IIA, dihydrotanshinone I, and TAN I, exhibit good anticancer activity in PCa. In this study, we review the progress of TAN compounds (cryptotanshinone, TAN IIA, dihydrotanshinone I, and TAN I) in treating PCa over the past decade. These compounds can act on the same molecular mechanisms, as they have a very similar structure; they are also found to work slightly differently in PCa. According to current studies, compared with other TAN compounds, TAN IIA appears to hold more potential for treating PCa. The toxicity, side effects or biodistribution of Salvia miltiorrhiza and these four TANs need to be confirmed with further research. Findings obtained in this study may provide important information for the potential clinical application of cryptotanshinone, TAN IIA, dihydrotanshinone I, and TAN I in the treatment of PCa.

Outpatient Patient Controlled Analgesia (PCA) for the Palliative Care Patient.

This study explores the under-researched domain of patient-controlled analgesia (PCA) for cancer pain management in adult outpatients, focusing on the transition from patient-controlled analgesia pumps (PCA pump) to oral medications. While existing literature primarily addresses the use of PCA in inpatient settings, this descriptive study investigates the initiation of outpatient PCA in palliative care patients. The retrospective chart review includes data from all admissions between July 1, 2014, and December 31, 2020. Among the 49 identified patients, 41 were admitted for cancer-related pain, with an indication for PCA such as insufficient pain relief, highly fluctuating pain, or inadequate response to other routes. Of these patients, 13 were successfully transitioned from outpatient PCA to oral opioids. The study underscores the effective use of PCA as a transitional tool following a pain crisis that necessitates inpatient admission. Future research avenues could explore healthcare utilization, length of stay, and required outpatient resources, such as home visits or telehealth, for optimal PCA use in outpatient settings.

Estimation of plant pollution removal capacity based on intensive air quality measurements.

This study investigated the role of present vegetation in improving air quality in Bucharest (Romania) by analyzing six years of air quality data (PM10 and NO2) from multiple monitoring stations. The target value for human health protection is regularly exceeded for PM10 and not for NO2 over time. Road traffic has substantially contributed (over 70%) to ambient PM10 and NO2 levels. The results showed high seasonal variations in pollutant concentrations, with a pronounced effect of vegetation in reducing PM10 and NO2 levels. Indeed, air quality improvements of 7% for PM10 and 25% for NO2 during the growing season were reported. By using Principal Component Analysis and pollution data subtraction methodology, we have disentangled the impact of vegetation on air pollution and observed distinct annual patterns, particularly higher differences in PM10 and NO2 concentrations during the warm season. Despite limitations such as a lack of full tree inventory for Bucharest and a limited number of monitoring stations, the study highlighted the efficiency of urban vegetation to mitigate air pollution.