Clinical study of steroid receptors in nonmuscle invasive bladder cancer: A domain worth revisiting.

Introduction: The prognostic significance of steroid receptors in bladder cancer remains controversial. This study was designed to determine the expression status of androgen receptor (AR), estrogen receptors (ERα and Erß), and its potential role in predicting survival in patients with nonmuscle invasive bladder cancer (NMIBC). Methods: Sixty patients of NMIBC were screened and 57 (41 males and 16 females) were included in our study. The tissue microarray slides were evaluated by pathologists blinded to the clinical information. Association of distribution of steroid receptors with stage, grade, progression, and recurrence was seen. Results: The mean age of the population was 60.9 ± 9.3 years. Pathologically, majority of the patients were Ta (Ta: T1 stage 61.4% vs. 38.6%). Nine (15.8%) of the tumors stained positive for AR while one (1.8%) tumor stained positive for ERα and 36 (63.2%) tumors stained for ERß. A higher proportion of male NMIBC stained positive for AR (19.5% vs. 6.2%, P = 0.420) while ERß positivity was higher in females (58.5% vs. and 75%,P = 0.247). AR-negative tumors showed higher recurrence (20/48%-42%) as compared to AR-positive tumors (2/9%-22%). ERß-positive tumors showed higher recurrence (15/36%-42% vs. 7/21%-33%, P = 0.179). Progression-free survival (PFS) was found to be significantly lower for ERß-negative group (log-rank test P = 0.035). Conclusion: AR and ERß positivity is found in NMIBC patients while ERα shows minimal staining in NMIBC patients. Although it did not reach a statistical significance, a higher proportion of AR-negative and ERß-positive tumors recurred as compared to AR-positive and ERß-negative patients. PFS was significantly lower in ERß-negative group. Further exploratory studies on larger sample sizes are required to validate these findings in NMIBC patients.

Enhancing photocatalytic degradation of quinoline by ZnO:TiO2 mixed oxide: Optimization of operating parameters and mechanistic study.

This study focuses on the photocatalytic degradation of quinoline, a recalcitrant heterocyclic nitrogenous aromatic organic compound, using the mixed oxide ZnO-TiO2 photo-catalyst. Photo-catalysts were synthesized by the solid-state reaction method at different calcination temperatures of 400 °C, 600 °C, and 800 °C. Different analytical methods, including Field emission scanning electron microscope, Brunauer-Emmett-Teller surface area, X-ray diffraction, UV-vis diffuse reflectance spectroscopy, Fourier-transform infrared spectroscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy analysis were used for the catalyst characterization. The highest pore surface area of 57.9 m2g-1 was obtained for the photo-catalyst calcined at 400 °C. The effects of calcination temperature, solution pH, initial concentration, catalyst dose as well as irradiation time were studied. At the optimum condition, i.e., calcination temperature of 400 °C, pH ≈8 and catalyst dose of 2.5 gL-1, maximum quinoline degradation and total organic carbon (TOC) removal efficiency of ≈92% and ≈78% were obtained after 240 min for initial quinoline amount of 50 mgL-1. The 1st, 2nd, and nth-order kinetic models were applied to analyze the quinoline degradation rate. The photocatalytic mechanism was studied by drawing energy level diagram with the help of the band-gap structures of the ZnO and TiO2, potential of the free radicals like OH and O2 and HOMO-LUMO energy gap of the quinoline molecule. The proposed pathways of quinoline mineralization were suggested on the basis of the identified intermediates by the gas chromatograph-mass spectrometer analysis and scavenger study.

Mechanistic evaluation of heterocyclic aromatic compounds mineralization by a Cu doped ZnO photo-catalyst.

In this study, Cu doped ZnO photo-catalysts were used for the degradation of the heterocyclic compounds, pyridine and quinoline. Three ZnO based photo-catalysts with different amounts of Cu doping (1%, 5% and 10%) were synthesized by precipitation method. The characterization of the catalyst was done using field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Brunauer Emmett Teller (BET), diffuse reflectance spectroscopy (DRS) and photo-luminescence (PL) techniques. The band gaps of the pure ZnO, and 1%, 5% and 10% Cu doped ZnO photo-catalysts were found to be 3.27 eV, 3.21 eV, 3.17 eV and 2.91 eV, respectively. The effects of pH, photo-catalyst dose and irradiation time were studied. Under optimum conditions (5% Cu doped ZnO, dose of 1.2 g L-1 for pyridine and 1.6 g L-1 for quinoline, pH = 11 and time = 5 h), the maximum pyridine and quinoline mineralization efficiencies were found to be 92.4% and 74.3%, respectively. The mineralization process followed first-order kinetics. The in situ formation of singlet oxygen, hydroxyl radicals and superoxide radicals was confirmed by reactive oxygen species (ROS) scavenger studies. Catalyst reusability studies showed excellent mineralization up to four consecutive cycles. The enhanced photo-catalytic mechanism was studied by comparing the band structure with respect to the potential of highly reactive species (˙OH and O2˙-). A possible mineralization pathway was proposed on the basis of the intermediates detected by gas chromatography coupled with mass spectrometry (GC-MS) analysis.

Biosorption of Heavy Metals from Aqueous Solution by Bacteria Isolated from Contaminated Soil.

This study was carried out to analyze the heavy metals biosorption potential of bacteria isolated from soil contaminated with electroplating industrial effluents. Bacterial isolates were screened for their multi-metal biosorption potential against copper, nickel, lead, and chromium. Bacterial isolate CU4A showed the maximum uptake of copper, nickel, lead, and chromium in aqueous solution, with a biosorption efficiency of 87.16 %, 79.62%, 84.92%, and 68.12%, respectively. The bacterial strain CU4A was identified as Bacillus cereus, following 16S rRNA gene sequence analysis. The surface chemical functional groups of bacterial biomass were identified by Fourier transform infrared (FTIR) spectroscopy as hydroxyl, carboxyl, amine, and halide, which may be involved in the biosorption of heavy metals. Analysis with scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) confirmed the adsorption of metals on the bacterial cell mass. The results of this study are significant and could be further investigated for the removal of heavy metals from contaminated environments.

Electronic Structures of Mono-Oxidized Copper and Nickel Phosphasalen Complexes.

Non-innocent ligands render the determination of the electronic structure in metal complexes difficult. As such, a combination of experimental techniques and quantum chemistry are required to correctly elucidate them. This paper deals with the one-electron oxidation of copper(II) and nickel(II) complexes featuring a phosphasalen ligand (Psalen), which differs from salen analogues by the presence of iminophosphorane groups (P=N) instead of imines. Various experimental techniques (X-ray diffraction, cyclic voltammetry, NMR, EPR, and UV/Vis spectroscopies, and magnetic measurements) as well as quantum chemical calculations were used to define the electronic structure of the oxidized complexes. These can be modified by a small change in the ligand structure, that is, the replacement of a tert-butyl group by a methoxy on the phenoxide ring. The different techniques have allowed quantifying the amount of spin density located on the metal center and on the Psalen ligands. All complexes were found to possess a multi-configurational ground state, in which the ratio of the +II versus +III oxidation state of the metal center, and therefore the phenolate versus phenoxyl radical ligand character, varies upon the substituents. The tert-butyl group favors a strong localization on the metal center whereas with the methoxy group the metallic configurations decrease and the ligand configurations increase. The importance of the geometrical considerations compared with the electronic substituent effect is highlighted by the differences observed between the solid-state (EPR, magnetic measurements) and solution characterizations (EPR and NMR data).

Nonsurgical Periodontal Therapy decreases the Severity of Rheumatoid Arthritis: A Case-control Study.

INTRODUCTION: Rheumatoid arthritis (RA) and periodontitis are common chronic inflammatory conditions. Several studies suggested a relationship between RA and periodontitis. Recent studies have shown a beneficial effect of periodontal treatment on the severity of active RA. So the aim of this study was to examine the effect of nonsurgical periodontal therapy on the clinical parameters of RA. MATERIALS AND METHODS: A total of 60 subjects with moderate-to-severe chronic generalized periodontitis and active RA in the age range 18 to 65 were selected for the study. They were divided into two groups. Group A (control group) consisted of 30 subjects with chronic generalized periodontitis and RA, and group B of 30 subjects with chronic generalized peri-odontitis and RA and they received nonsurgical periodontal therapy (scaling, root planning, and oral hygiene instructions). Evaluation of clinical observations of Simplified Oral Hygiene Index (OHI-S), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD), clinical attachment level (CAL), number of swollen joints (SJ), number of tender joints (TJ), values of erythrocyte sedimentation rate (ESR), visual analogue scale (VAS) for patient's global assessment, 3 months disease activity score (DAS) index, and C-reactive protein (CRP) was done at baseline and 3 months. Statistical evaluation of clinical observations was carried out. RESULTS: Group B subjects who received nonsurgical periodon-tal therapy showed statistically significant improvement in all periodontal and RA parameters at 3 months, compared with group A who did not receive periodontal therapy. CONCLUSION: It can be concluded from the result that nonsurgical periodontal therapy may contribute to reduction in severity and symptoms of RA. CLINICAL SIGNIFICANCE: Rheumatoid arthritis patients should be evaluated for periodontitis and treated for the same in order to reduce its severity level.

Expression of SOD and APX genes positively regulates secondary cell wall biosynthesis and promotes plant growth and yield in Arabidopsis under salt stress.

Abiotic stresses cause accumulation of reactive oxygen species (ROS), such as hydrogen peroxide (H2O2) in plants. Sophisticated mechanisms are required to maintain optimum level of H2O2 that acts as signalling molecule regulating adaptive response to salt stress. CuZn-superoxide dismutase (CuZn-SOD) and ascorbate peroxidase (APX) constitute first line of defence against oxidative stress. In the present study, PaSOD and RaAPX genes from Potentilla atrosanguinea and Rheum australe, respectively were overexpressed individually as well as in combination in Arabidopsis thaliana. Interestingly, PaSOD and dual transgenic lines exhibit enhanced lignin deposition in their vascular bundles with altered S:G ratio under salt stress. RNA-seq analysis revealed that expression of PaSOD gene in single and dual transgenics positively regulates expression of lignin biosynthesis genes and transcription factors (NACs, MYBs, C3Hs and WRKY), leading to enhanced and ectopic deposition of lignin in vascular tissues with larger xylem fibres and alters S:G ratio, as well. In addition, transgenic plants exhibit growth promotion, higher biomass production and increased yield under salt stress as compared to wild type plants. Our results suggest that in dual transgenics, ROS generated during salt stress gets converted into H2O2 by SOD and its optimum level was maintained by APX. This basal level of H2O2 acts as messenger for transcriptional activation of lignin biosynthesis in vascular tissue, which provides mechanical strength to plants. These findings reveal an important role of PaSOD and RaAPX in enhancing salt tolerance of transgenic Arabidopsis via increased accumulation of compatible solutes and by regulating lignin biosynthesis.

Analyzing Global Cancer Control: Progress of National Cancer Control Programs through Composite Indicators and Regression Modeling.

Aim: Cancer is a significant public health concern, and National Cancer Control Programs (NCCPs) are crucial for reducing its burden. However, assessing the progress of NCCPs is challenging due to the complexity of cancer control outcomes and the various factors that influence them. Composite indicators can provide a comprehensive and accurate assessment of NCCP progress. Materials and Methods: The dataset was compiled for 144 countries and comprised eight composite indices and two high-level comparative indicators (mortality-to-cancer incidence ratio [MIR] and 5-year cancer prevalence-to-incidence ratio [PCIR]) representing NCCP outcomes. Two large databases and six annual composite index reports were consulted. Linear regression analysis and Pearson correlation coefficients were used to establish a relationship between indicators and NCCP outcomes. A multiple regression machine learning model was generated to further improve the accuracy of NCCP outcome prediction. Results: High-income countries had the highest cancer incidence, whereas low-income countries had the highest MIR. Linear regression analysis indicated a negative trend between all composite indicators and MIR, whereas a positive trend was observed with PCIR. The Human Development Index and the Legatum Prosperity Index had the highest adjusted R 2 values for MIR (0.74 and 0.73) and PCIR (0.86 and 0.81), respectively. Multiple linear regression modeling was performed, and the results indicated a low mean squared error score (-0.02) and a high R 2 score (0.86), suggesting that the model accurately predicts NCCP outcomes. Conclusions: Overall, composite indicators can be an effective tool for evaluating NCCP, and the results of this study can aid in the development and keeping track of NCCP progress for better cancer control.

Effect of K+ Force Fields on Ionic Conductivity and Charge Dynamics of KOH in Ethylene Glycol.

Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion-ion and ion-solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K+ ion. Diffusion-based Nernst-Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.

Role of Intermolecular Interactions in Deep Eutectic Solvents for CO2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies.

Recent research and reviews on CO2 capture methods, along with advancements in industry, have highlighted high costs and energy-intensive nature as the primary limitations of conventional direct air capture and storage (DACS) methods. In response to these challenges, deep eutectic solvents (DESs) have emerged as promising absorbents due to their scalability, selectivity, and lower environmental impact compared to other absorbents. However, the molecular origins of their enhanced thermal stability and selectivity for DAC applications have not been explored before. Therefore, the current study focuses on a comprehensive investigation into the molecular interactions within an alkaline DES composed of potassium hydroxide (KOH) and ethylene glycol (EG). Combining Fourier transform infrared (FT-IR) and quantum chemical calculations, the study reports structural changes and intermolecular interactions induced in EG upon addition of KOH and its implications on CO2 capture. Experimental and computational spectroscopic studies confirm the presence of noncovalent interactions (hydrogen bonds) within both EG and the KOH-EG system and point to the aggregation of ions at higher KOH concentrations. Additionally, molecular electrostatic potential (MESP) surface analysis, natural bond orbital (NBO) analysis, quantum theory of atoms-in-molecules (QTAIM) analysis, and reduced density gradient-noncovalent interaction (RDG-NCI) plot analysis elucidate changes in polarizability, charge distribution, hydrogen bond types, noncovalent interactions, and interaction strengths, respectively. Evaluation of explicit and hybrid models assesses their effectiveness in representing intermolecular interactions. This research enhances our understanding of molecular interactions in the KOH-EG system, which are essential for both the absorption and desorption of CO2. The study also aids in predicting and selecting DES components, optimizing their ratios with salts, and fine-tuning the properties of similar solvents and salts for enhanced CO2 capture efficiency.

Precursor engineering for soft selective synthesis of phase pure metal-rich digenite (Cu9S5) and djurleite (Cu31S16) nanocrystals and investigation of their photo-switching characteristics.

Copper sulfide nanostructures have evolved as one of the most technologically important materials for energy conversion and storage owing to their economic and non-toxic nature and superior performances. This paper presents a direct, scalable synthetic route aided by a single source molecular precursor (SSP) approach to access copper sulfide nanomaterials. Two SSPs, CuX(dmpymSH)(PPh3)2 (where X = Cl or I), were synthesized in quantitative yields and thermolyzed under appropriate conditions to afford the nanostructures. The analysis of the nanostructures through pXRD, EDS and XPS suggested that phase pure digenite (Cu9S5) and djurleite (Cu31S16) nanostructures were isolated from -Cl and -I substituted SSPs, respectively. The morphologies of the as-synthesized nanomaterials were investigated using electron microscopy techniques (SEM and TEM). DRS studies on pristine materials revealed blue shifted optical band gaps, which were found to be optimum for photoelectrochemical application. A prototype photoelectrochemical cell fabricated using the pristine nanostructures exhibited a stable photo-switching property, which presents these materials as suitable economic and environmentally friendly photon absorber materials.

Comprehensive transcriptomic study on horse gram (Macrotyloma uniflorum): De novo assembly, functional characterization and comparative analysis in relation to drought stress.

BACKGROUND: Drought tolerance is an attribute maintained in plants by cross-talk between multiple and cascading metabolic pathways. Without a sequenced genome available for horse gram, it is difficult to comprehend such complex networks and intercalated genes associated with drought tolerance of horse gram (Macrotyloma uniflorum). Therefore, de novo transcriptome discovery and associated analyses was done for this highly drought tolerant yet under exploited legume to decipher its genetic makeup. RESULTS: Eight samples comprising of shoot and root tissues of two horse gram genotypes (drought-sensitive; M-191 and drought-tolerant; M-249) were used for comparison under control and polyethylene glycol-induced drought stress conditions. Using Illumina sequencing technology, a total of 229,297,896 paired end read pairs were generated and utilized for de novo assembly of horse gram. Significant BLAST hits were obtained for 26,045 transcripts while, 3,558 transcripts had no hits but contained important conserved domains. A total of 21,887 unigenes were identified. SSRs containing sequences covered 16.25% of the transcriptome with predominant tri- and mono-nucleotides (43%). The total GC content of the transcriptome was found to be 43.44%. Under Gene Ontology response to stimulus, DNA binding and catalytic activity was highly expressed during drought stress conditions. Serine/threonine protein kinase was found to dominate in Enzyme Classification while pathways belonging to ribosome metabolism followed by plant pathogen interaction and plant hormone signal transduction were predominant in Kyoto Encyclopedia of Genes and Genomes analysis. Independent search on plant metabolic network pathways suggested valine degradation, gluconeogenesis and purine nucleotide degradation to be highly influenced under drought stress in horse gram. Transcription factors belonging to NAC, MYB-related, and WRKY families were found highly represented under drought stress. qRT-PCR validated the expression profile for 9 out of 10 genes analyzed in response to drought stress. CONCLUSIONS: De novo transcriptome discovery and analysis has generated enormous information over horse gram genomics. The genes and pathways identified suggest efficient regulation leading to active adaptation as a basal defense response against drought stress by horse gram. The knowledge generated can be further utilized for exploring other underexploited plants for stress responsive genes and improving plant tolerance.

Customizing Treatment Scheduling Windows with a Time Margin Recipe: A Single-institutional Study.

Purpose: Rising cancer incidences, complex treatment techniques, and workflows have all impacted the radiotherapy scheduling process. Intelligent appointment scheduling is needed to help radiotherapy users adapt to new practices. Materials and Methods: We utilized van Herk's safety margin formula to determine the radiotherapy department's treatment scheduling window (TSW). In addition, we examined the influence of in-room imaging on linac occupancy time (LOT). Varian Aria™ software version 15.1 was used to collect retrospective data on LOT, treatment site, intent, techniques, special protocol, and in-room imaging. Results: Treatment scheduling windows varied across treatment sites. The mean TSW using van Herk's formalism was 31.5 min, significantly longer than the current TSW of 15 min (P = 0.036), with the pelvic site having the longest (43.8 min) and the brain site having the shortest (12 min). 28% of patients exceeded the in-practice TSW of 15 min. 46.2% of patients had multiple images per fraction, with the proportion being highest in pelvic patients (33%). Patients treated with palliative intent, intensity-modulated radiotherapy, special protocols (bladder protocol and gating), and multiple in-room images per fraction had significantly higher LOT. High treatment time uncertainty was observed in the pelvic and thorax sites, indicating the impact of in-room imaging frequency and on-couch treatment decisions on overall treatment time and indicating that current treatment practices should be reviewed and modified if necessary. Conclusions: The time margin recipe can customize the treatment scheduling window and improve treatment practices. This formalism can help manage the radiotherapy department's workload and reduce patient wait times.

Efficient and Reliable Data Extraction in Radiation Oncology using Python Programming Language: A Pilot Study.

Background and Purpose: In recent years, data science approaches have entered health-care systems such as radiology, pathology, and radiation oncology. In our pilot study, we developed an automated data mining approach to extract data from a treatment planning system (TPS) with high speed, maximum accuracy, and little human interaction. We compared the amount of time required for manual data extraction versus the automated data mining technique. Materials and Methods: A Python programming script was created to extract specified parameters and features pertaining to patients and treatment (a total of 25 features) from TPS. We successfully implemented automation in data mining, utilizing the application programming interface environment provided by the external beam radiation therapy equipment provider for the whole group of patients who were accepted for treatment. Results: This in-house Python-based script extracted selected features for 427 patients in 0.28 ± 0.03 min with 100% accuracy at an astonishing rate of 0.04 s/plan. Comparatively, manual extraction of 25 parameters took an average of 4.5 ± 0.33 min/plan, along with associated transcriptional and transpositional errors and missing data information. This new approach turned out to be 6850 times faster than the conventional approach. Manual feature extraction time increased by a factor of nearly 2.5 if we doubled the number of features extracted, whereas for the Python script, it increased by a factor of just 1.15. Conclusion: We conclude that our in-house developed Python script can extract plan data from TPS at a far higher speed (>6000 times) and with the best possible accuracy compared to manual data extraction.

Cost effective media optimization for PHB production by Bacillus badius MTCC 13004 using the statistical approach.

Polyhydroxybutyrate (PHB) has significant potential for replacing non-biodegradable traditional plastic, which is responsible for several global environmental issues. The main problem with switching to bio-based alternatives for petrochemical plastics is the large price gap on the market. To overcome this problem, the present research was focused on the utilization of inexpensive substrates i.e. agricultural residues for cost-effective PHB production by endospore-forming bacteria Bacillus badius MTCC 13004. For efficient PHB production, Box-Behnken Design (BBD) was selected for media optimization and to observe the interactive effects of four variables i.e. pH, Na acetate, Banana peel, and mustard cake. PHB yield of 2.11 g/L was attained under optimized conditions compared to non-optimized conditions (0.72 g/L). FTIR spectra analysis of PHB extracted from Bacillus badius was found to be similar to commercial PHB. NMR data was also matched with the chemical shift signals CH, CH2, and CH3 of PHB. The melting temperature (Tm) and glass transition temperature (Tg) of PHB from Bacillus badius was found to be 165.14 and 2.68 °C, respectively. Further, PCR protocol was also designed to amplify key enzymes of the PHB synthesis pathway i.e. PHB synthase (phb C gene).

Controlled synthesis of photoresponsive bismuthinite (Bi2S3) nanostructures mediated through a new 1D bismuth-pyrimidylthiolate coordination polymer as a molecular precursor.

Bismuthinite (Bi2S3) nanostructures have garnered significant interest due to their appealing photoresponsivity which has positioned them as an attractive choice for energy conversion applications. However, to utilize their full potential, a simple and economically viable method of preparation is highly desirable. Herein, we present the synthesis and characterization including structural elucidation of a new air- and moisture-stable bismuth-pyrimidylthiolate complex. This complex serves as an efficient single-source molecular precursor for the facile preparation of phase-pure Bi2S3 nanostructures. Powder X-ray diffraction (PXRD), Raman spectroscopy, electron dispersive spectroscopy (EDS) and electron microscopy techniques were used to assess the crystal structure, phase purity, elemental composition and morphology of the as-prepared nanostructures. This study also revealed the profound effects of temperature and growth duration on the crystallinity, phase formation and morphology of nanostructures. The optical band gap of the nanostructures was tuned within the range of 1.9-2.3 eV, which is blue shifted with respect to the bulk bandgap and suitable for photovoltaic applications. Liquid junction photo-electrochemical cells fabricated from the as-prepared Bi2S3 nanostructure exhibit efficient photoresponsivity and good photo-stability, which project them as promising candidates for alternative low-cost photon absorber materials.

Accuracy of combined multi-parametric MRI and PSMA PET-CT in diagnosing localized prostate cancer: newer horizons for a biopsy-free pathway.

INTRODUCTION: Prostate-specific antigen (PSA) is a reliable biomarker for identification of prostate cancer, although a biopsy is still the gold standard for detecting prostate cancer. Similar to higher PIRADS lesions on MRI, the maximal standard uptake value (SUV max) on PSMA PET is linked to a higher likelihood of prostate cancer. Can an mpMRI in conjunction with PSMA PET Scan accurately predict prostate cancer and further trigger omission of biopsy similar to other solid organ urological malignancies? METHODS: Ga-68 PSMA PET and mpMRI were performed for each patient who was a part of this retrospective study. The PET-positive lesion's maximum standardized uptake value (SUVmax) was recorded. Prostate biopsies were performed on patients who had PSMA PET avid lesions and a PIRADS score of 4 or 5. Robot-assisted radical prostatectomy (RARP) was afterward performed on patients who had cancer on their prostate biopsy. The prostatectomy specimen's histopathological information was recorded. Cutoff values and correlations between the variables were determined using the ROC curves and Pearson's correlation test. RESULT: On the basis of suspicious DRE findings or elevated PSA, 70 men underwent mpMRI and PET scans. PIRADS 4 patients had a median (IQR) SUVmax of 8.75 (11.95); whereas, PIRADS 5 patients had an SUVmax of 24.5 (22). The mean SUVmax for patients whose biopsies revealed no cancer was 6.25 ± 1.41. With an AUC of 0.876 on the ROC curve, it was found that there was a significant positive correlation between the results of the mpMRI and PET scans and those of the histopathological investigation. A SUVmax ≥ 8.25 on PSMA PET for a PIRADS 4/5 lesion on mpMRI will aid in correctly predicting malignancy, with a sensitivity of 82.8% and specificity of 100%. CONCLUSION: The findings of this study were positive and indicated that patients with a high suspicion of prostate cancer on mpMRI and PSMA PET (PIRADS ≥ 4 and SUVmax ≥ 8.25). This study substantiates the fact that a combination of mpMRI and PSMA PET can accurately predict localized prostate cancer.

Comparison of modified Glasgow-Imrie, Ranson, and Apache II scoring systems in predicting the severity of acute pancreatitis.

<b>Aim:</b> The course of acute pancreatitis is variable with patients at risk of poor outcomes. The purpose of this study was to compare Modified Glasgow-Imrie, Ranson, and APACHE II scoring systems in predicting the severity of acute pancreatitis. </br></br> <b> Material and Methods: </b> After a brief history, clinical examination and qualifying inclusion criteria, 70 patients (41 women, 29 men) diagnosed with acute pancreatitis were included in the study. The three scores were calculated for each patient and evaluated for their role in the assessment of specific outcomes. </br></br> <b>Results:</b> 34.3% patients were diagnosed with severe acute pancreatitis, while 65.7% patients had mild acute pancreatitis. A strong positive correlation was found between all the prognostic scores and the severity of disease. In the prediction of the severity of disease according to AUC, it was found that Glasgow-Imrie score had an AUC of 0.864 (0.7560.973), followed very closely by APACHE II score with an AUC of 0.863 (0.7580.968). APACHE II had the highest sensitivity (79.17%) in predicting severity while Glasgow-Imrie score was the most specific (97.83%) of all the scores. Patients with a Glasgow-Imrie score above the cut-off value of 3 had more complications and a longer hospital stay. </br></br> <b>Conclusion:</b> The Glasgow-Imrie score was comparable to APACHE II score and better than Ranson score statistically in predicting the severity of acute pancreatitis. Its administration in predicting the severity of acute pancreatitis is recommended.

An audit of Grade III or more skin reactions in consecutively assessed patients at a modern radiation oncology center.

Purpose: Radiation dermatitis is most common and debilitating side effects of radiotherapy leading to treatment interruption, thereby compromising the local control, and effecting quality of life. With the invent of modern imaging and recent advances in megavoltage radiotherapy, radiation-related side effects have reduced. In this audit, we report the risk factors associated with Grade III dermatitis in modern centers. Materials and Methods: We analyzed 172 patients treated with volume modulated arc therapy (VMAT) and static field intensity-modulated radiotherapy (SFIMRT) at our center. All head and neck, breast, gynecological, GU malignancies, and sarcoma patients treated with a dose of >45 Gy from April 2018 to December 2019 were included in the study. On couch, treatment verification was done with cone-beam computer tomography (CBCT). Slice-by-slice verification of planning target volume (PTV) with CBCT was done in the first three fractions and weekly thereafter. Skin evaluation was done using CTCAE v. 5. Statistical analysis was done using SPSS v. 22. Results: Of the 172 patients treated with VMAT and SFIMRT, 15 patients (8.7%) had Grade III dermatitis. Grade III dermatitis was mostly seen in breast cancer followed by head-and-neck patients. More reactions were observed in patients with advanced stage disease. Treatment verification is important at the later course of treatment, especially in head-and-neck cases where the treatment volume is large and PTV may extend outside skin. Contributing factors of radiation dermatitis at modern radiotherapy center are gene mutation, use of concurrent chemoradiotherapy, and bolus. Conclusion: We hereby conclude that PTV mismatch in weekly treatment verification, genetic mutations, concurrent chemo-radiotherapy, use of thermoplastic mask, and bolus are the contributing factors for Grade III dermatitis in modern radiotherapy centers.