PD-L1 and nectin-4 expression and genomic characterization of bladder cancer with divergent differentiation.

BACKGROUND: Bladder cancer with divergent differentiation (BCDD) comprises a heterogenous group of tumors with a poor prognosis, and differential expression of nectin-4 and programmed death ligand-1 (PD-L1) has been reported in BCDD. Importantly, nectin-4 expression in bladder cancer is associated with response to enfortumab vedotin, and PD-L1 expression is associated with responses to immune checkpoint inhibitors (ICIs). METHODS: The authors conducted a retrospective review identifying 117 patients with advanced or metastatic BCDD who were treated at Winship Cancer Institute from 2011 to 2021. They performed immunohistochemistry staining for nectin-4 and PD-L1 expression by histologic subtype as well as genomic analysis of these patients, including RNA sequencing, whole-exome sequencing, and fusion detection analysis as well as a subgroup genomic analysis of patients with BCDD who received ICIs. RESULTS: The results indicated that nectin-4 expression was highest in the groups who had the squamous and plasmacytoid subtypes, whereas the group that had the sarcomatoid subtype (70.8%) had the highest proportion of PD-L1-positive patients. Genomic analysis yielded several key findings, including a 50% RB1 mutation rate in patients who had small cell BCDD, targetable PIK3CA mutations across multiple subtypes of BCDD, and significantly higher expression of TEC in responders to ICIs. CONCLUSIONS: In this study, the authors identified clinically relevant data on nectin-4 and PD-L1 expression in patients with rare bladder tumors. They also identified several novel findings in the genomic analysis that highlight the role of precision medicine in this population of patients. Larger, prospective studies are needed to validate these hypothesis-generating data.

Prevention of Brain Metastases: A New Frontier.

This review discusses the topic of prevention of brain metastases from the most frequent solid tumor types, i.e., lung cancer, breast cancer and melanoma. Within each tumor type, the risk of brain metastasis is related to disease status and molecular subtype (i.e., EGFR-mutant non-small cell lung cancer, HER2-positive and triple-negative breast cancer, BRAF and NRAF-mutant melanoma). Prophylactic cranial irradiation is the standard of care in patients in small cell lung cancer responsive to chemotherapy but at the price of late neurocognitive decline. More recently, several molecular agents with the capability to target molecular alterations driving tumor growth have proven as effective in the prevention of secondary relapse into the brain in clinical trials. This is the case for EGFR-mutant or ALK-rearranged non-small cell lung cancer inhibitors, tucatinib and trastuzumab-deruxtecan for HER2-positive breast cancer and BRAF inhibitors for melanoma. The need for screening with an MRI in asymptomatic patients at risk of brain metastases is emphasized.

Matrix stiffness influences response to chemo and targeted therapy in brain metastatic breast cancer cells.

Breast cancer is the most common malignancy accounting for 12.5% of all newly diagnosed cancer cases across the globe. Breast cancer cells are known to metastasize to distant organs (i.e., brain), wherein they can exhibit a dormant phenotype for extended time periods. These dormant cancer cells exhibit reduced proliferation and therapeutic resistance. However, the mechanisms by which dormant cancer cells exhibit resistance to therapy, in the context of brain metastatic breast cancer (BMBC), is not well understood. Herein, we utilized hyaluronic acid (HA) hydrogels with varying stiffnesses to study drug responsiveness in dormant vs. proliferative BMBC cells. It was found that cells cultured on soft HA hydrogels (∼0.4 kPa) that showed a non-proliferative (dormant) phenotype exhibited resistance to Paclitaxel or Lapatinib. In contrast, cells cultured on stiff HA hydrogels (∼4.5 kPa) that showed a proliferative phenotype exhibited responsiveness to Paclitaxel or Lapatinib. Moreover, dormancy-associated resistance was found to be due to upregulation of the serum/glucocorticoid regulated kinase 1 (SGK1) gene which was mediated, in part, by the p38 signaling pathway. Accordingly, SGK1 inhibition resulted in a dormant-to-proliferative switch and response to therapy. Overall, our study demonstrates that matrix stiffness influences dormancy-associated therapy response mediated, in part, via the p38/SGK1 axis.

Laminin I mediates resistance to lapatinib in HER2-positive brain metastatic breast cancer cells in vitro.

The role of extracellular matrix (ECM) prevalent in the brain metastatic breast cancer (BMBC) niche in mediating cancer cell growth, survival, and response to therapeutic agents is not well understood. Emerging evidence suggests a vital role of ECM of the primary breast tumor microenvironment (TME) in tumor progression and survival. Possibly, the BMBC cells are also similarly influenced by the ECM of the metastatic niche; therefore, understanding the effect of the metastatic ECM on BMBC cells is imperative. Herein, we assessed the impact of various ECM components (i.e., Tenascin C, Laminin I, Collagen I, Collagen IV, and Fibronectin) on brain metastatic human epidermal growth factor receptor 2 (HER2)-positive and triple negative breast cancer (TNBC) cell lines in vitro. The highly aggressive TNBC cell line was minimally affected by ECM components exhibiting no remarkable changes in viability and morphology. On the contrary, amongst various ECM components tested, the HER2-positive cell line was significantly affected by Laminin I with higher viability and demonstrated a distinct spread morphology. In addition, HER2-positive BMBC cells exhibited resistance to Lapatinib in presence of Laminin I. Mechanistically, Laminin I-induced resistance to Lapatinib was mediated in part by phosphorylation of Erk 1/2 and elevated levels of Vimentin. Laminin I also significantly enhanced the migratory potential and replicative viability of HER2-positive BMBC cells. In sum, our findings show that presence of Laminin I in the TME of BMBC cells imparts resistance to targeted therapeutic agent Lapatinib, while increasing the possibility of its dispersal and clonogenic survival.

Glioblastoma mechanobiology at multiple length scales.

Glioblastoma multiforme (GBM), a primary brain cancer, is one of the most aggressive forms of human cancer, with a very low patient survival rate. A characteristic feature of GBM is the diffuse infiltration of tumor cells into the surrounding brain extracellular matrix (ECM) that provide biophysical, topographical, and biochemical cues. In particular, ECM stiffness and composition is known to play a key role in controlling various GBM cell behaviors including proliferation, migration, invasion, as well as the stem-like state and response to chemotherapies. In this review, we discuss the mechanical characteristics of the GBM microenvironment at multiple length scales, and how biomaterial scaffolds such as polymeric hydrogels, and fibers, as well as microfluidic chip-based platforms have been employed as tissue mimetic models to study GBM mechanobiology. We also highlight how such tissue mimetic models can impact the field of GBM mechanobiology.

Distortionless, free-breathing, and respiratory resolved 3D diffusion weighted imaging of the abdomen.

PURPOSE: Abdominal imaging is frequently performed with breath holds or respiratory triggering to reduce the effects of respiratory motion. Diffusion weighted sequences provide a useful clinical contrast but have prolonged scan times due to low signal-to-noise ratio (SNR), and cannot be completed in a single breath hold. Echo-planar imaging (EPI) is the most commonly used trajectory for diffusion weighted imaging but it is susceptible to off-resonance artifacts. A respiratory resolved, three-dimensional (3D) diffusion prepared sequence that obtains distortionless diffusion weighted images during free-breathing is presented. Techniques to address the myriad of challenges including: 3D shot-to-shot phase correction, respiratory binning, diffusion encoding during free-breathing, and robustness to off-resonance are described. METHODS: A twice-refocused, M1-nulled diffusion preparation was combined with an RF-spoiled gradient echo readout and respiratory resolved reconstruction to obtain free-breathing diffusion weighted images in the abdomen. Cartesian sampling permits a sampling density that enables 3D shot-to-shot phase navigation and reduction of transient fat artifacts. Theoretical properties of a region-based shot rejection are described. The region-based shot rejection method was evaluated with free-breathing (normal and exaggerated breathing), and respiratory triggering. The proposed sequence was compared in vivo with multishot DW-EPI. RESULTS: The proposed sequence exhibits no evident distortion in vivo when compared to multishot DW-EPI, robustness to B0 and B1 field inhomogeneities, and robustness to motion from different respiratory patterns. CONCLUSION: Acquisition of distortionless, diffusion weighted images is feasible during free-breathing with a b-value of 500 s/mm2, scan time of 6 min, and a clinically viable reconstruction time.

Protocol for generating dormant human brain metastatic breast cancer spheroids in vitro.

Here, we present a protocol to generate dormant brain metastatic breast cancer (BMBC) spheroids utilizing hyaluronic acid (HA) hydrogels. We describe the steps for construction of spheroids from human BMBC cell lines MDA-MB-231Br and BT474Br3, HA hydrogel preparation, and spheroid plating on HA hydrogels and in suspension culture. We then detail the impact of HA hydrogel on the dormant phenotype of spheroids by measuring spheroid cross-sectional area, cell numbers, and EdU staining. For complete details on the use and execution of this protocol, please refer to Kondapaneni et al.1.

Linear Muscle Segmentation for Metastatic Renal Cell Carcinoma: Changes in Clinic-Friendly Estimation Predict Survival Following Cytoreductive Nephrectomy.

INTRODUCTION: Baseline sarcopenia and postoperative changes in muscle mass are independently associated with overall survival (OS) in patients with metastatic renal cell carcinoma (mRCC) undergoing cytoreductive nephrectomy (CN). Here we examine the relationships between preoperative (baseline), postoperative changes in muscle quantity, and survival outcomes following CN as determined by linear segmentation, a clinic-friendly tool that rapidly estimates muscle mass. MATERIALS AND METHODS: Our nephrectomy database was reviewed for patients with metastatic disease who underwent CN for RCC. Linear segmentation of the bilateral psoas/paraspinal muscles was completed for baseline imaging within 60 days of surgery and imaging 30 to 365 days postoperatively. Kruskal-Wallis for numerical and Fisher's exact test for categorical variables were used to test for differences between groups according to percent change in linear muscle index (LMI, cm2/m2). Multivariable Cox proportional hazards models evaluated associations between LMI percent change and cancer-specific (CSM) and all-cause mortality (ACM). Kaplan Meier curves estimated cancer-specific (CSS) and overall survival (OS). RESULTS: From 2004-2020, 205 patients were included of whom 52 demonstrated stable LMI (25.4%; LMI change < 5% [0Δ]), 60 increase (29.3%; LMI +5% [+Δ]), and 92 decrease (44.9%; LMI -5% [-Δ]). Median time from baseline imaging to surgery was 18 days, and time from surgery to postoperative imaging was 133 days. Median CSS and OS were highest among patients with 0Δ LMI (CSS: 133.6 [0Δ] vs. 61.9 [+Δ] vs. 37.4 [-Δ] months; P = .0018 || OS: 67.2 [0Δ] vs. 54.8 [+Δ] vs. 29.5 [-Δ] months; P = .0007). Stable LMI was a protective factor for CSM (HR 0.48; P = .024) and ACM (HR 0.59; P = .040) on multivariable analysis. DISCUSSION: Change in muscle mass after CN, as measured by the linear muscle segmentation technique, is independently associated with OS and CSS in patients following CN. Of note, lack of change was associated with longer survival.

Structure-guided mutagenesis of Henipavirus receptor-binding proteins reveals molecular determinants of receptor usage and antibody-binding epitopes.

Nipah virus (NiV) is a highly lethal, zoonotic Henipavirus (HNV) that causes respiratory and neurological signs and symptoms in humans. Similar to other paramyxoviruses, HNVs mediate entry into host cells through the concerted actions of two surface glycoproteins: a receptor-binding protein (RBP) that mediates attachment and a fusion glycoprotein (F) that triggers fusion in an RBP-dependent manner. NiV uses ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3) as entry receptors. Ghana virus (GhV), a novel HNV identified in a Ghanaian bat, uses EFNB2 but not EFNB3. In this study, we employ a structure-informed approach to identify receptor-interfacing residues and systematically introduce GhV-RBP residues into a NiV-RBP backbone to uncover the molecular determinants of EFNB3 usage. We reveal two regions that severely impair EFNB3 binding by NiV-RBP and EFNB3-mediated entry by NiV pseudotyped viral particles. Further analyses uncovered two-point mutations (NiVN557SGhV and NiVY581TGhV) pivotal for this phenotype. Moreover, we identify NiV interaction with Y120 of EFNB3 as important for the usage of this receptor. Beyond these EFNB3-related findings, we reveal two domains that restrict GhV binding of EFNB2, confirm the HNV-head as an immunodominant target for polyclonal and monoclonal antibodies, and describe putative epitopes for GhV- and NiV-specific monoclonal antibodies. Cumulatively, the work presented here generates useful reagents and tools that shed insight to residues important for NiV usage of EFNB3, reveal regions critical for GhV binding of EFNB2, and describe putative HNV antibody-binding epitopes. IMPORTANCE: Hendra virus and Nipah virus (NiV) are lethal, zoonotic Henipaviruses (HNVs) that cause respiratory and neurological clinical features in humans. Since their initial outbreaks in the 1990s, several novel HNVs have been discovered worldwide, including Ghana virus. Additionally, there is serological evidence of zoonotic transmission, lending way to concerns about future outbreaks. HNV infection of cells is mediated by the receptor-binding protein (RBP) and the Fusion protein (F). The work presented here identifies NiV RBP amino acids important for the usage of ephrin-B3 (EFNB3), a receptor highly expressed in neurons and predicted to be important for neurological clinical features caused by NiV. This study also characterizes epitopes recognized by antibodies against divergent HNV RBPs. Together, this sheds insight to amino acids critical for HNV receptor usage and antibody binding, which is valuable for future studies investigating determinants of viral pathogenesis and developing antibody therapies.

Tracking Health Beyond Recovery: A Study on Identifying Post-COVID Syndrome Symptoms.

Context: The COVID-19 pandemic had a profound global impact, leaving a lasting legacy in the form of post-COVID syndrome. This condition, experienced after recovering from the virus, manifests in symptoms, such as fatigue, cough, shortness of breath, joint pain, and brain fog, highlighting the virus's lingering influence on the human body. Aim: To Identify post-COVID syndrome symptoms among COVID-19 recovered patients from Karad Taluka. Materials and methods: A study involving 228 COVID-19-recovered individuals from a Karad tertiary care hospital used consecutive sampling. Data were collected via structured questionnaires, focused on post-COVID syndrome symptoms. Statistical analysis used: Frequency and percentage were used to analyze the presence of post-COVID syndrome symptoms. Results: A total of 228 COVID-19-recovered individuals were included in the study, of whom 53% were male and 47% were female. Most of the study subjects had 25 (10.9%) mild, 138 (60.5%) moderate, and 65 (28.5%) severe symptoms. Symptom-wise, the majority of the subjects experienced symptoms: fatigue 116 (50.8% moderate), shortness of breath 135 (58.3% moderate), cough 116 (50.8%), sore throat 115 (50.4% mild), chest pain (57% mild), joint pain 151 (66.2% severe), brain fog 103 (45% severe). Most (43%) experienced symptoms for 12 months, that is, 1 year. Conclusion: The results depict the recovered individuals continue to experience symptoms. The most common symptoms are fatigue, shortness of breath, and cough in varied severity (from mild, moderate, and severe). How to cite this article: Walvekar SS, Mohite VR. Tracking Health Beyond Recovery: A Study on Identifying Post-COVID Syndrome symptoms. Indian J Crit Care Med 2024;28(2):170-174.

Ultrastructural and immunohistochemical insights on the anti-glioma effects of a dual-drug cocktail in an in vivo experimental model.

Glioma coined as 'butterfly tumor' exhibits intense heterogeneity at the molecular and cellular levels. Although, Temozolomide exerted a long-ranging and prevailing therapeutic effect against glioma, albeit it has provided modest survival outcome. Fucoidan, (marine brown algal derivative) has demonstrated potent anti-tumor effects including glioma. Nevertheless, there is paucity of studies conducted on Fucoidan to enhance the anti-glioma efficacy of Temozolomide. The present study aimed to explore the plausible synergistic anti-glioma efficacy of Fucoidan in combination with Temozolomide in an in vivo experimental model. The dual-drug combination significantly inhibited tumor growth in in vivo and prolonged the survival rate when compared with the other treatment and tumor-control groups, via down-regulation of inflammatory cascade- IL-6/T LR4 and JAK/STAT3 as per the immunohistochemistry findings. Furthermore, the ultrastructural analysis indicated that the combinatorial treatment had restored the normal neuronal architecture of glioma-induced rats. Overall, the dual-drug cocktail might enhance the therapeutic outcome in glioma patients.

Valorization of coffee bean processing waste for bioethanol production: comparison and evaluation of mass transfer effects in fermentations using free and encapsulated cells of Saccharomyces cerevisiae.

Coffee husk, an agricultural waste abundant in carbohydrates and nutrients, is typically discarded through landfills, mixed with animal fodder, or incinerated. However, in alignment with sustainable development principles, researchers worldwide are exploring innovative methods to harness the value of coffee husk, transforming it into profitable products. One such avenue is the biotechnological approach to bioethanol production from agricultural wastes, offering an eco-friendly alternative to mitigate the adverse effects of fossil fuels. This study delves into the feasibility of utilizing coffee husk as a substrate for bioethanol production, employing and comparing various hydrolysis methods. The enzymatic hydrolysis method outshone thermochemical and thermal approaches, yielding 1.84 and 3.07 times more reducing sugars in the hydrolysate, respectively. In examining bioethanol production, a comparison between free and encapsulated cells in enzyme hydrolysate revealed that free-cell fermentation faced challenges due to cell viability issues. Under specific fermentation conditions, bioethanol yield (0.59 and 0.83 g of bioethanol/g of reducing sugar) and productivity (0.1 and 0.12 g/L h) were achieved for free and encapsulated cells, respectively. However, it was noted that bioethanol production by encapsulated cells was more significantly influenced by internal mass transfer effects, as indicated by the Thiele modulus and effectiveness factor. In conclusion, our findings underscore the potential of coffee husk as a valuable substrate for bioethanol production, showcasing its viability in contributing to sustainable and eco-friendly practices.

2018 Leibovich prognostic model for renal cell carcinoma: Performance in a large population with special consideration of Black race.

BACKGROUND: The 2018 Leibovich prognostic model for nonmetastatic renal cell carcinoma (RCC) combines clinical, surgical, and pathologic factors to predict progression-free survival (PFS) and cancer-specific survival (CSS) for patients with clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC) histology. Despite high accuracy, <1% of the original cohort was Black. Here, the authors examined this model in a large population with greater Black patient representation. METHODS: By using a prospectively maintained RCC institutional database, patients were assigned Leibovich model risk scores. Survival outcomes included 5-year and 10-year PFS and CSS. Prognostic accuracy was determined using area under the curve (AUC) analysis and calibration plots. Black patient subanalyses were conducted. RESULTS: In total, 657 (29%) of 2295 patients analyzed identified as Black. Declines in PFS and CSS were observed as scores increased. Discrimination for ccRCC was strong for PFS (AUC: 5-year PFS, 0.81; 10-year PFS, 0.78) and for CSS (AUC: 5-year CSS, 0.82; 10-year CSS, 0.74). The pRCC AUC for PFS was 0.74 at 5 years and 0.71 at 10 years; and the AUC for CSS was 0.74 at 5 years and 0.70 at 10 years. In chRCC, better performance was observed for CSS (AUC at 5 years, 0.75) than for PFS (AUC: 0.66 at 5 years; 0.55 at 10 years). Black patient subanalysis revealed similar-to-improved performance for ccRCC at 5 years (AUC: PFS, 0.79; CSS, 0.87). For pRCC, performance was lower for PFS (AUC at 5 years, 0.63) and was similar for CSS (AUC at 5 years, 0.77). Sample size limited Black patient 10-year and chRCC analyses. CONCLUSIONS: The authors externally validated the 2018 Leibovich RCC prognostic model and found optimal performance for ccRCC, followed by pRCC, and then chRCC. Importantly, the results were consistent in this large representation of Black patients. PLAIN LANGUAGE SUMMARY: In 2018, a model to predict survival in patients with renal cell carcinoma (kidney cancer) was introduced by Leibovich et al. This model has performed well; however, Black patients have been under-represented in examination of its performance. In this study, 657 Black patients (29%) were included, and the results were consistent. This work is important for making sure the model can be applied to all patient populations.

Varying the RGD concentration on a hyaluronic acid hydrogel influences dormancy versus proliferation in brain metastatic breast cancer cells.

A majority of breast cancer deaths occur due to metastasis of cancer cells to distant organs. In particular, brain metastasis is very aggressive with an extremely low survival rate. Breast cancer cells that metastasize to the brain can enter a state of dormancy, which allows them to evade death. The brain microenvironment provides biophysical, biochemical, and cellular cues, and plays an important role in determining the fate of dormant cancer cells. However, how these cues influence dormancy remains poorly understood. Herein, we employed hyaluronic acid (HA) hydrogels with a stiffness of ~0.4 kPa as an in vitro biomimetic platform to investigate the impact of biochemical cues, specifically alterations in RGD concentration, on dormancy versus proliferation in MDA-MB-231Br brain metastatic breast cancer cells. We applied varying concentrations of RGD peptide (0, 1, 2, or 4 mg/mL) to HA hydrogel surfaces and confirmed varying degrees of surface functionalization using a fluorescently labeled RGD peptide. Post functionalization, ~10,000 MDA-MB-231Br cells were seeded on top of the hydrogels and cultured for 5 days. We found that an increase in RGD concentration led to changes in cell morphology, with cells transitioning from a rounded to spindle-like morphology as well as an increase in cell spreading area. Also, an increase in RGD concentration resulted in an increase in cell proliferation. Cellular dormancy was assessed using the ratio of phosphorylated extracellular signal-regulated kinase 1/2 (p-ERK) to phosphorylated p38 (p-p38) positivity, which was significantly lower in hydrogels without RGD and in hydrogels with lowest RGD concentration compared to hydrogels functionalized with higher RGD concentration. We also demonstrated that the HA hydrogel-induced cellular dormancy was reversible. Finally, we demonstrated the involvement of ß1 integrin in mediating cell phenotype in our hydrogel platform. Overall, our results provide insight into the role of biochemical cues in regulating dormancy versus proliferation in brain metastatic breast cancer cells.

Unveiling the anti-glioma potential of a marine derivative, Fucoidan: its synergistic cytotoxicity with Temozolomide-an in vitro and in silico experimental study.

Glioma coined as a "butterfly" tumor associated with a dismal prognosis. Marine algal compounds with the richest sources of bioactive components act as significant anti-tumor therapeutics. However, there is a paucity of studies conducted on Fucoidan to enhance the anti-glioma efficacy of Temozolomide. Therefore, the present study aimed to evaluate the synergistic anti-proliferative, anti-inflammatory and pro-apoptotic effects of Fucoidan with Temozolomide in in vitro and in silico experimental setup. The anti-proliferative effects of Temozolomide and Fucoidan were evaluated on C6 glioma cells by MTT and migration assay. Modulation of inflammatory markers and apoptosis induction was affirmed at the morphological and transcriptional level by dual staining and gene expression. Molecular docking (MD) and molecular dynamics simulation (MDS) studies were performed against the targets to rationalize the inhibitory effect. The dual-drug combination significantly reduced the cell viability and migration of glioma cells in a synergistic dose-dependent manner. At the molecular level, the dual-drug combination significantly down-regulated inflammatory genes with a concomitant upregulation of pro-apoptotic marker. In consensus with our in vitro findings, molecular docking and simulation studies revealed that the anti-tumor ligands: Temozolomide, Fucoidan with 5-(3-Methy1-trizeno)-imidazole-4-carboxamide (MTIC), and 4-amino-5-imidazole-carboxamide (AIC) had the potency to bind to the inflammatory proteins at their active sites, mediated by H-bonds and other non-covalent interactions. The dual-drug combinatorial treatment synergistically inhibited the proliferation, migration of glioma cells and promoted apoptosis; conversely with the down-regulation of inflammatory genes. However, pre-clinical experimental evidence is warranted for the possible translation of this combination. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03814-6.

Polymeric architecture as a tool for controlling the reactivity of palladium(II) loaded nanoreactors.

Self-assembled systems, like polymeric micelles, have become great facilitators for conducting organic reactions in aqueous media due to their broad potential applications in green chemistry and biomedical applications. Massive strides have been taken to improve the reaction scope of such systems, enabling them to perform bioorthogonal reactions for prodrug therapy. Considering these significant advancements, we sought to study the relationships between the architecture of the amphiphiles and the reactivity of their PdII loaded micellar nanoreactors in conducting depropargylation reactions. Towards this goal, we designed and synthesized a series of isomeric polyethylene glycol (PEG)-dendron amphiphiles with different dendritic architectures but with an identical degree of hydrophobicity and hydrophilic to lipophilic balance (HLB). We observed that the dendritic architecture, which serves as the main binding site for the PdII ions, has greater influence on the reactivity than the hydrophobicity of the dendron. These trends remained constant for two different propargyl caged substrates, validating the obtained results. Density functional theory (DFT) calculations of simplified models of the dendritic blocks revealed the different binding modes of the various dendritic architectures to PdII ions, which could explain the observed differences in the reactivity of the nanoreactors with different dendritic architectures. Our results demonstrate how tuning the internal architecture of the amphiphiles by changing the orientation of the chelating moieties can be used as a tool for controlling the reactivity of PdII loaded nanoreactors.

Creatinine to Cystatin-C Ratio in Renal Cell Carcinoma: A Clinically Pragmatic Prognostic Factor and Sarcopenia Biomarker.

INTRODUCTION: Low creatinine to cystatin-C ratio (Cr/Cys-C) may be a biomarker for low-muscle mass. Furthermore, low Cr/Cys-C is associated with decreased overall survival (OS), but to date, has not been examined in patients with renal cell carcinoma (RCC). Our objective is to evaluate associations between low Cr/Cys-C ratio and OS and recurrence-free survival (RFS) in patients with RCC treated with nephrectomy. METHODS: We performed a retrospective review of patients with RCC treated with nephrectomy. Patients with end-stage renal disease and less than 1-year follow up were excluded. Cr/Cys-C was dichotomized at the median for the cohort (low vs. high). OS and RFS for patients with high versus low Cr/Cys-C were estimated with the Kaplan-Meier method, and associations with the outcomes of interest were modeled using Cox proportional Hazards models. Associations between Cr/Cys-C and skeletal muscle mass were assessed with correlations and logistic regression. RESULTS: A total of 255 patients were analyzed, with a median age of 64. Median (IQR) Cr/Cys-C was 1 (0.8-1.2). Low Cr/Cys-C was associated with age, female sex, Eastern Cooperative Oncology Group Performance Status ≥1, TNM stage, and tumor size. Kaplan-Meier and Cox regression analysis demonstrated an association between low Cr/Cys-C and decreased OS (HR = 2.97, 95%CI, 1.12-7.90, P =0.029) and RFS (HR = 3.31, 95%CI, 1.26-8.66, P = .015). Furthermore, a low Cr/Cys-C indicated a 2-3 increase in risk of radiographic sarcopenia. CONCLUSIONS: Lower Cr/Cys-C is associated with inferior oncologic outcomes in RCC and, pending validation, may have utility as a serum biomarker for the presence of sarcopenia in patients with RCC treated with nephrectomy.

Accelerating High b-Value Diffusion-Weighted MRI Using a Convolutional Recurrent Neural Network (CRNN-DWI).

PURPOSE: To develop a novel convolutional recurrent neural network (CRNN-DWI) and apply it to reconstruct a highly undersampled (up to six-fold) multi-b-value, multi-direction diffusion-weighted imaging (DWI) dataset. METHODS: A deep neural network that combines a convolutional neural network (CNN) and recurrent neural network (RNN) was first developed by using a set of diffusion images as input. The network was then used to reconstruct a DWI dataset consisting of 14 b-values, each with three diffusion directions. For comparison, the dataset was also reconstructed with zero-padding and 3D-CNN. The experiments were performed with undersampling rates (R) of 4 and 6. Standard image quality metrics (SSIM and PSNR) were employed to provide quantitative assessments of the reconstructed image quality. Additionally, an advanced non-Gaussian diffusion model was employed to fit the reconstructed images from the different approaches, thereby generating a set of diffusion parameter maps. These diffusion parameter maps from the different approaches were then compared using SSIM as a metric. RESULTS: Both the reconstructed diffusion images and diffusion parameter maps from CRNN-DWI were better than those from zero-padding or 3D-CNN. Specifically, the average SSIM and PSNR of CRNN-DWI were 0.750 ± 0.016 and 28.32 ± 0.69 (R = 4), and 0.675 ± 0.023 and 24.16 ± 0.77 (R = 6), respectively, both of which were substantially higher than those of zero-padding or 3D-CNN reconstructions. The diffusion parameter maps from CRNN-DWI also yielded higher SSIM values for R = 4 (>0.8) and for R = 6 (>0.7) than the other two approaches (for R = 4, <0.7, and for R = 6, <0.65). CONCLUSIONS: CRNN-DWI is a viable approach for reconstructing highly undersampled DWI data, providing opportunities to reduce the data acquisition burden.

Repurposing synthetic and natural derivatives induces apoptosis in an orthotopic glioma-induced xenograft model by modulating WNT/ß-catenin signaling.

BACKGROUND: Glioblastomas arise from multistep tumorigenesis of the glial cells. Despite the current state-of-art treatment, tumor recurrence is inevitable. Among the innovations blooming up against glioblastoma, drug repurposing could provide profound premises for treatment enhancement. While considering this strategy, the efficacy of the repurposed drugs as monotherapies were not up to par; hence, the focus has now shifted to investigate the multidrug combinations. AIM: To investigate the efficacy of a quadruple-combinatorial treatment comprising temozolomide along with chloroquine, naringenin, and phloroglucinol in an orthotopic glioma-induced xenograft model. METHODS: Antiproliferative effect of the drugs was assessed by immunostaining. The expression profiles of WNT/ß-catenin and apoptotic markers were evaluated by qRT-PCR, immunoblotting, and ELISA. Patterns of mitochondrial depolarization was determined by flow cytometry. TUNEL assay was performed to affirm apoptosis induction. In vivo drug detection study was carried out by ESI-Q-TOF MS analysis. RESULTS: The quadruple-drug treatment had significantly hampered glioma proliferation and had induced apoptosis by modulating the WNT/ß-catenin signaling. Interestingly, the induction of apoptosis was associated with mitochondrial depolarization. The quadruple-drug cocktail had breached the blood-brain barrier and was detected in the brain tissue and plasma samples. CONCLUSION: The quadruple-drug combination served as a promising adjuvant therapy to combat glioblastoma lethality in vivo and can be probed for translation from bench to bedside.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene.

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.