Impact of Obesity-Related Endoplasmic Reticulum Stress on Cancer and Associated Molecular Targets.

Obesity, characterized by excessive body fat, is closely linked to endoplasmic reticulum (ER) stress, leading to insulin resistance and type 2 diabetes. Inflammatory pathways like c-Jun N-terminal kinase (JNK) worsen insulin resistance, impacting insulin signaling. Moreover, ER stress plays a substantial role in cancer, influencing tumor cell survival and growth by releasing factors like vascular endothelial growth factor (VEGF). The unfolded protein response (UPR) is pivotal in this process, offering both pro-survival and apoptotic pathways. This review offers an extensive exploration of the sophisticated connection between ER stress provoked by obesity and its role in both the onset and advancement of cancer. It delves into the intricate interplay between oncogenic signaling and the pathways associated with ER stress in individuals who are obese. Furthermore, this review sheds light on potential therapeutic strategies aimed at managing ER stress induced by obesity, with a focus on addressing cancer initiation and progression. The potential to alleviate ER stress through therapeutic interventions, which may encompass the use of small molecules, FDA-approved medications, and gene therapy, holds great promise. A more in-depth examination of pathways such as UPR, ER-associated protein degradation (ERAD), autophagy, and epigenetic regulation has the potential to uncover innovative therapeutic approaches and the identification of predictive biomarkers.

Resveratrol-based Delivery Systems as Contemporary Nominees for Combating Pulmonary Diseases: A Comprehensive Review.

Exploiting different formulation approaches, each designed to improve the clinical use of resveratrol (RES) in treating several lung diseases. Accentuating the rationale for using RESbased delivery systems in different clinical applications in pulmonary diseases. Resveratrol (RES), a well-known natural polyphenol stilbenoid, possesses tremendous potential to treat various lung diseases owing to its anti-inflammatory, antioxidant, antiapoptotic, antiviral, and anticancer activities. Its physicochemical properties have restricted the beneficial activities of resveratrol, as it is characterized by low aqueous solubility, bioavailability and stability in addition to high photosensitivity. With the growing understanding of the effectiveness of RES in treating lung diseases, the need for attempts and advances in RES formulations should be evolved to enhance its involvement in pharmaceutical applications. This review discusses the role of RES in treating several pulmonary illnesses. For the first time, different approaches and strategies to evade its limitations and allow its clinical applications via various routes for managing a variety of respiratory ailments are presented rigorously.

Hepatocellular carcinoma patients serum modulates the regenerative capacities of adipose mesenchymal stromal cells.

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers causing the highest mortality rate worldwide. Treatment options of surgery, radiation, cytotoxic drugs and liver transplantation suffer significant side effects and a high frequency of relapse. Stem cell therapy has been proposed as a new effective therapy, however, controversial reports are emerging on the role of mesenchymal stem cells in cancer. In this work, we aimed to assess the regenerative capacities of adipose mesenchymal stem cells when exposed to serum from HCC patients, by assessing the effect of the sera on modulating the regenerative capacities of h-AMSCs and the cancer properties in HCC cells. This will pave the way for maximizing the efficacy of MSCs in cancer therapy. Our data show that HCC serum-treated hA-MSCs suffered oncogene-induced senescence as shown by their altered morphology and ameliorated proliferation and differentiation. The cells were enlarged with small irregular nuclei, swollen rough endoplasmic reticulum cisternae, and aging lysosomes typified by dark residual bodies. HCC serum-treated Huh-7 cancer cells on the other hand displayed higher tumor aggressiveness as depicted by altered morphology, increased cellular proliferation and migration, and decreased percentage of early and late apoptotic cells. Our findings provide evidence that exposure of hA-MSCs to the serum of HCC patients decreases their regenerative capacities and should be considered when employed as a potential therapy in HCC patients.

Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.

Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts' evaluation of segmentation quality. The experimental results revealed a low interrater agreement (Krippendorff α, 0.34) in experts' segmentation quality perception. Furthermore, the correlations between the ratings and commonly used quantitative quality metrics were low (Kendall tau between Dice score and mean rating, 0.23; Kendall tau between Hausdorff distance and mean rating, 0.51), with large variability among the experts. Conclusion The results demonstrate that quality ratings are prone to variability due to the ambiguity of tumor boundaries and individual perceptual differences, and existing metrics do not capture the clinical perception of segmentation quality. Keywords: Brain Tumor Segmentation, Deep Learning Algorithms, Glioblastoma, Cancer, Machine Learning Clinical trial registration nos. NCT00756106 and NCT00662506 Supplemental material is available for this article. © RSNA, 2023.

Bioproduction and optimization of newly characterized melanin pigment from Streptomyces djakartensis NSS-3 with its anticancer, antimicrobial, and radioprotective properties.

BACKGROUND: Melanin is a natural pigment that is considered a promising biomaterial for numerous biotechnological applications across several industries. Melanin has biomedical applications as antimicrobial, anticancer, and antioxidant properties. Additionally, in the pharmaceutical and cosmetic industries, it is used in drug delivery and as a radioprotective agent. Also, melanin has environmental uses in the fields of bioremediation and the food industry. The biosynthesis of melanin pigment is an area of interest for researchers due to its multifunctionality, high compatibility, and biodegradability. Therefore, our present work is the first attempt to characterize and optimize the productivity of melanin pigment from Streptomyces djakartensis NSS-3 concerning its radioprotection and biological properties. RESULTS: Forty isolates of soil actinobacteria were isolated from the Wadi Allaqui Biosphere Reserve, Egypt. Only one isolate, ACT3, produced a dark brown melanin pigment extracellularly. This isolate was identified according to phenotypic properties and molecular phylogenetic analysis as Streptomyces djakartensis NSS-3 with accession number OP912881. Plackett-Burman experimental design (PBD) and response surface methodology (RSM) using a Box-Behnken design (BBD) were performed for optimum medium and culturing conditions for maximum pigment production, resulting in a 4.19-fold improvement in melanin production (118.73 mg/10 mL). The extracted melanin pigment was purified and characterized as belonging to nitrogen-free pyomelanin based on ultraviolet-visible spectrophotometry (UV-VIS), Fourier transform infrared (FT-IR), Raman spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and NMR studies. Purified melanin demonstrated potent scavenging activity with IC50 values of 18.03 µg/mL and revealed high potency as sunscreens (in vitro SPF = 18.5). Moreover, it showed a nontoxic effect on a normal cell line (WI38), while it had a concentration-dependent anticancer effect on HCT116, HEPG, and MCF7 cell lines with IC50 = 108.9, 43.83, and 81.99 µg/mL, respectively. Also, purified melanin had a detrimental effect on the tested MDR bacterial strains, of which PA-09 and SA-04 were clearly more susceptible to melanin compared with other strains with MICs of 6.25 and 25 µg/mL, respectively. CONCLUSION: Our results demonstrated that the newly characterized pyomelanin from Streptomyces djakartensis NSS-3 has valuable biological properties due to its potential photoprotective, antioxidant, anticancer, antimicrobial, and lack of cytotoxic activities, which open up new prospects for using this natural melanin pigment in various biotechnological applications and avoiding chemical-based drugs.

Thymoquinone-protoflavone hybrid molecules as potential antitumor agents.

We describe herein the synthesis of eight new ester-coupled hybrid compounds from thymoquinone and protoflavone building blocks, and their bioactivity testing against multiple cancer cell lines. Among the hybrids, compound 14 showed promising activities in all cell lines studied. The highest activities were recorded against breast cancer cell lines with higher selectivity to MDA-MB-231 as compared to MCF-7. Even though the hybrids were found to be completely hydrolysed in 24 h under cell culture conditions, compound 14 demonstrated a ca. three times stronger activity against U-87 glioblastoma cells than a 1:1 mixture of its fragments. Further, compound 14 showed good tumour selectivity: it acted 4.4-times stronger on U-87 cells than on MRC-5 fibroblasts. This selectivity was much lower, only ca. 1.3-times, when the cells were co-treated with a 1:1 mixture of its non-coupled fragments. Protoflavone-thymoquinone hybrids may therefore serve as potential new antitumor leads particularly against glioblastoma.

Magnetic resonance imaging of pilonidal sinus disease: interobserver agreement and practical MRI reporting tips.

OBJECTIVE: To evaluate the interobserver agreement for the features of natal cleft pilonidal sinus disease (PSD) on magnetic resonance imaging (MRI) and propose a standardized checklist for reporting PSD on MRI. MATERIALS AND METHODS: Forty MRI studies of 39 discrete patients with PSD were retrospectively evaluated by five independent radiologists using a standardized checklist. Fleiss' Kappa (k) coefficients of agreement were used to test the agreement between categorical variables. The MRI features of the natal cleft sepsis associated with PSD were classified into four main categories: morphology, branching and extensions, external skin openings, and the relationship of the PSD to the coccyx. A survey was created and disseminated online among general surgeons who treat patients with PSD to assess the relevance of the MRI features proposed in the standardized checklist. RESULTS: The overall agreement regarding the identification of morphology of the natal cleft sepsis was moderate (k = 0.59). Lateral and caudal extensions interobserver agreement was substantial (k = 0.64 and 0.71, respectively). However, the overall agreement regarding the individual parts of anal sphincter involved was moderate (k = 0.47). Substantial interobserver agreement was found in assessing the proximity of the PSD to the coccyx (k = 0.62). CONCLUSION: Preoperative MRI can delineate the extensions and branching of PSD with substantial agreement. MRI is superior in describing the deep extensions of PSD with better reliability than assessing the number and locations of the external openings. Expert consensus agreement is needed to establish the MRI features necessary for optimal reporting of PSD. CLINICAL RELEVANCE STATEMENT: MRI can offer valuable information about the extent of sepsis associated with pilonidal sinus disease, particularly in cases with involvement of critical anatomical structures such as the coccyx and anal triangle. MRI can potentially contribute to more accurate patient stratification and surgical planning. KEY POINTS: • The interobserver agreement for assessing PSD's lateral and caudal extension on MRI is substantial. • MRI can describe deep extensions and branching of PSD with superior reliability than assessing the number and site of external openings. • Reporting the relationship between natal cleft sepsis in PSD and the anal region may influence the surgical approach and postoperative healing.

Investigation of autosegmentation techniques on T2-weighted MRI for off-line dose reconstruction in MR-linac workflow for head and neck cancers.

BACKGROUND: In order to accurately accumulate delivered dose for head and neck cancer patients treated with the Adapt to Position workflow on the 1.5T magnetic resonance imaging (MRI)-linear accelerator (MR-linac), the low-resolution T2-weighted MRIs used for daily setup must be segmented to enable reconstruction of the delivered dose at each fraction. PURPOSE: In this pilot study, we evaluate various autosegmentation methods for head and neck organs at risk (OARs) on on-board setup MRIs from the MR-linac for off-line reconstruction of delivered dose. METHODS: Seven OARs (parotid glands, submandibular glands, mandible, spinal cord, and brainstem) were contoured on 43 images by seven observers each. Ground truth contours were generated using a simultaneous truth and performance level estimation (STAPLE) algorithm. Twenty total autosegmentation methods were evaluated in ADMIRE: 1-9) atlas-based autosegmentation using a population atlas library (PAL) of 5/10/15 patients with STAPLE, patch fusion (PF), random forest (RF) for label fusion; 10-19) autosegmentation using images from a patient's 1-4 prior fractions (individualized patient prior [IPP]) using STAPLE/PF/RF; 20) deep learning (DL) (3D ResUNet trained on 43 ground truth structure sets plus 45 contoured by one observer). Execution time was measured for each method. Autosegmented structures were compared to ground truth structures using the Dice similarity coefficient, mean surface distance (MSD), Hausdorff distance (HD), and Jaccard index (JI). For each metric and OAR, performance was compared to the inter-observer variability using Dunn's test with control. Methods were compared pairwise using the Steel-Dwass test for each metric pooled across all OARs. Further dosimetric analysis was performed on three high-performing autosegmentation methods (DL, IPP with RF and 4 fractions [IPP_RF_4], IPP with 1 fraction [IPP_1]), and one low-performing (PAL with STAPLE and 5 atlases [PAL_ST_5]). For five patients, delivered doses from clinical plans were recalculated on setup images with ground truth and autosegmented structure sets. Differences in maximum and mean dose to each structure between the ground truth and autosegmented structures were calculated and correlated with geometric metrics. RESULTS: DL and IPP methods performed best overall, all significantly outperforming inter-observer variability and with no significant difference between methods in pairwise comparison. PAL methods performed worst overall; most were not significantly different from the inter-observer variability or from each other. DL was the fastest method (33 s per case) and PAL methods the slowest (3.7-13.8 min per case). Execution time increased with a number of prior fractions/atlases for IPP and PAL. For DL, IPP_1, and IPP_RF_4, the majority (95%) of dose differences were within ± 250 cGy from ground truth, but outlier differences up to 785 cGy occurred. Dose differences were much higher for PAL_ST_5, with outlier differences up to 1920 cGy. Dose differences showed weak but significant correlations with all geometric metrics (R2 between 0.030 and 0.314). CONCLUSIONS: The autosegmentation methods offering the best combination of performance and execution time are DL and IPP_1. Dose reconstruction on on-board T2-weighted MRIs is feasible with autosegmented structures with minimal dosimetric variation from ground truth, but contours should be visually inspected prior to dose reconstruction in an end-to-end dose accumulation workflow.

Utility of Tumor Mutational Burden as a Biomarker for Response to Immune Checkpoint Inhibition in the VA Population.

PURPOSE: Immune checkpoint inhibitors (ICIs) are used for an increasing number of indications across various tumor types, as well as several tumor-agnostic indications in patients with advanced cancer. Although many patients benefit from ICI therapy, others do not, highlighting a need for better predictive biomarkers. Tumor mutational burden (TMB) reflects the global number of mutations within a tumor and has been widely explored as a predictive biomarker of ICI response. The current tumor type-agnostic US Food and Drug Administration approval of pembrolizumab for metastatic solid tumors defines high TMB (TMB-H) as ≥10 mut/Mb as measured by FoundationOne CDx. This fixed cutoff may not be the ideal value across all solid tumors. METHODS: We performed a retrospective analysis of the association of survival outcomes with TMB in patients treated with ICI for five major cancer types, using real-world data from the VA. Survival was measured from initiation of ICI, and Kaplan-Meier survival curves were compared by log-rank test. RESULTS: Overall survival (OS) was significantly longer for patients with TMB-H versus TMB low tumors in non-small-cell lung cancer (NSCLC; n = 1,593), head and neck (H&N) cancer (n = 222), and urothelial cancer (n = 332). OS was not significantly different based on TMB status in melanoma (n = 207) or esophageal/gastric cancer (n = 248). CONCLUSION: Consistent with previous studies, a predictive value of TMB ≥10 mut/Mb for ICI response was found in NSCLC and H&N, but not in esophageal/gastric cancer. Although inconclusive in the literature, significant association was found in urothelial cancer. The predictive value of TMB in melanoma was inconclusive. Our analysis does not support the use of a fixed threshold for TMB as a standalone predictive biomarker for ICI across all solid tumors.

Development and implementation of optimized endogenous contrast sequences for delineation in adaptive radiotherapy on a 1.5T MR-linear-accelerator: a prospective R-IDEAL stage 0-2a quantitative/qualitative evaluation of in vivo site-specific quality-assurance using a 3D T2 fat-suppressed platform for head and neck cancer.

Purpose: To improve segmentation accuracy in head and neck cancer (HNC) radiotherapy treatment planning for the 1.5T hybrid magnetic resonance imaging/linear accelerator (MR-Linac), three-dimensional (3D), T2-weighted, fat-suppressed magnetic resonance imaging sequences were developed and optimized. Approach: After initial testing, spectral attenuated inversion recovery (SPAIR) was chosen as the fat suppression technique. Five candidate SPAIR sequences and a nonsuppressed, T2-weighted sequence were acquired for five HNC patients using a 1.5T MR-Linac. MR physicists identified persistent artifacts in two of the SPAIR sequences, so the remaining three SPAIR sequences were further analyzed. The gross primary tumor volume, metastatic lymph nodes, parotid glands, and pterygoid muscles were delineated using five segmentors. A robust image quality analysis platform was developed to objectively score the SPAIR sequences on the basis of qualitative and quantitative metrics. Results: Sequences were analyzed for the signal-to-noise ratio and the contrast-to-noise ratio and compared with fat and muscle, conspicuity, pairwise distance metrics, and segmentor assessments. In this analysis, the nonsuppressed sequence was inferior to each of the SPAIR sequences for the primary tumor, lymph nodes, and parotid glands, but it was superior for the pterygoid muscles. The SPAIR sequence that received the highest combined score among the analysis categories was recommended to Unity MR-Linac users for HNC radiotherapy treatment planning. Conclusions: Our study led to two developments: an optimized, 3D, T2-weighted, fat-suppressed sequence that can be disseminated to Unity MR-Linac users and a robust image quality analysis pathway that can be used to objectively score SPAIR sequences and can be customized and generalized to any image quality optimization protocol. Improved segmentation accuracy with the proposed SPAIR sequence will potentially lead to improved treatment outcomes and reduced toxicity for patients by maximizing the target coverage and minimizing the radiation exposure of organs at risk.

Clinical Outcomes With a Fully Magnetically Levitated Left Ventricular Assist Device Among Women and Men.

BACKGROUND: Left ventricular assist devices (LVADs) are underused among women with advanced heart failure, but reasons remain unclear. Outcomes in women compared with men with contemporary fully magnetically levitated LVADs remain uncertain. OBJECTIVES: The authors examined differences in characteristics, 2-year outcomes, and risk for key adverse events among women and men. METHODS: In 2,200 HeartMate3 (HM3) (Abbott Cardiovascular) LVAD recipients in the MOMENTUM 3 study (Multicenter Study of MagLev Technology in Patients Undergoing Mechanical Circulatory Support Therapy with HeartMate 3), survival free of disabling stroke or reoperation to replace or remove a malfunctioning pump at 2 years was analyzed between women and men. Other outcomes included overall 2-year survival, adverse events, and functional measures. RESULTS: Women comprised 20.4% (n = 448 of 2,200) of the study population and were younger, with nonischemic cardiomyopathy, and more often were Black persons compared with men. The primary endpoint (women 79.4% vs men 75.5% (adjusted [a]HR: 0.96 [95% CI: 0.75-1.24]; P = 0.66) or survival at 2 years (women 82.4% vs men 80.2%; aHR: 1.06 [95% CI: 0.81-1.40]; P = 0.66) was no different. Women had an increased rate of stroke (adjusted incidence rate ratio [aIRR]: 1.52 [95% CI: 1.09-2.11]; P = 0.012), major bleeding (aIRR: 1.28 [95% CI: 1.15-1.42]; P < 0.0001) and infection (aIRR 1.14 [95% CI: 1.03-1.55]; P = 0.01), but these differences were not seen among older (>65 years) patients. Both groups had similar gains in 6-minute walk distance and quality-of-life measurements. CONCLUSIONS: There were no differences in the primary composite endpoint or overall survival in women compared with men at 2 years of support. Reasons underlying increase in hemocompatibility-related events and infection-related morbidity in younger women deserves further study. (MOMENTUM 3 IDE [HM3], NCT02224755; MOMENTUM 3 Continued Access Protocol [MOMENTUM 3 CAP], NCT02892955).

Benzene Amide Ether Scaffold is Active against Non-replicating and Intracellular Mycobacterium tuberculosis.

New drugs to treat tuberculosis which target intractable bacterial populations are required to develop shorter and more effective treatment regimens. The benzene amide ether scaffold has activity against intracellular Mycobacterium tuberculosis, but low activity against extracellular, actively replicating M. tuberculosis. We determined that these molecules have bactericidal activity against non-replicating M. tuberculosis but not actively replicating bacteria. Exposure to compounds depleted ATP levels in non-replicating bacteria and increased the oxygen consumption rate; a subset of molecules led to the accumulation of intrabacterial reactive oxygen species. A comprehensive screen of M. tuberculosis strains identified a number of under-expressing strains as more sensitive to compounds under replicating conditions including QcrA and QcrB hypomorphs. We determined the global gene expression profile after compound treatment for both replicating and nutrient-starved M. tuberculosis. We saw compound-dependent changes in the expression of genes involved in energy metabolism under both conditions. Taken together, our data suggest that the scaffold targets respiration in M. tuberculosis.

Synthesis of New Monoazo Disperse Dyes for Dyeing Polyester Fabric Using Two Different Dyeing Methods: Demonstration of Their Antibacterial and Anticancer Activities.

3-(dimethylamino)-1-phenylprop-2-en-1-ones were obtained with good yields by reacting dimethylformamide dimethylacetal with different methyl ketones. 3-oxo-3-phenyl-2-(2-phenylhydrazono)propanals disperse dyes were obtained via reacting of 3-(dimethylamino)-1-phenylprop-2-en-1-ones with phenyldiazonium chloride. The novel dyes were used in dyeing polyester fabrics through two different dyeing methods at temperatures of 100 and 130 °C. We found that the color strength when using the dyeing method at 130 °C was better than the dyeing method at 100 °C. The fastness properties of dyed fabrics with these new disperse dyes were studied and gave very good results (except for fastness to light, which gave moderate results). The new dyes were evaluated against some different types of bacteria and cancer, which showed excellent and promising results for the possibility of using these dyes as antibacterial and anticancer agents.

Risk Factors Associated With Sentinel Lymph Node Metastasis in Clinically Node-Negative Breast Cancer.

Objective: Sentinel lymph node biopsy (SLNB) is the standard of care for axillary staging in clinically node negative breast cancer. If predictive factors for sentinel lymph node (SLN) metastasis could be identified, it would allow selection of candidates for SLNB and omit axillary surgery in those with the lowest risk of axillary lymph node involvement. The aim of this study was to determine risk factors associated with SLN metastasis in breast cancer patients in Bahrain. Materials and Methods: Patients with clinically node-negative breast cancer who underwent SLNB at a single institution between 2016 and 2022 were identified from the pathology database. Patients who had failure of localization of SLN, those with bilateral cancers and those treated for a local recurrence were excluded. Results: A total of 160 breast cancer patients were retrospectively analyzed. Of these, 64.4% had a negative SLNB and 21.9% of all cases underwent axillary dissection. The following parameters emerged as predictors of SLN metastasis in univariate analysis: age; tumour grade; ER status; presence of lymphovascular invasion (LVI) and tumor size. On multivariate analysis, age was not independently associated with the incidence of SLN metastasis. Conclusion: This study showed that high tumour grades, presence of LVI and large tumour size were all risk factors related to axillary metastasis after SLNB in breast cancer. In the elderly, the incidence of SLN metastasis appeared to be relatively low, providing an opportunity to de-escalate axillary surgery in these patients. These findings may allow for the development of a nomogram to estimate the risk of SLN metastasis.

Customizable resveratrol spray-dried micro-composites for inhalation as a promising contender for treatment of idiopathic pulmonary fibrosis.

The past decades have witnessed tremendous expansion in utilization of plant-derived medicines as resveratrol (RES) in treating several diseases like idiopathic pulmonary fibrosis (IPF). RES can exhibit its role in treating IPF via its outstanding antioxidant and anti-inflammatory activities. The goal of this work was to formulate RES-loaded spray-dried composite microparticles (SDCMs) suitable for pulmonary delivery via dry powder inhaler (DPI). They were prepared by spray drying of a previously prepared RES-loaded bovine serum albumin nanoparticles (BSA NPs) dispersion using different carriers. RES-loaded BSA NPs, prepared by the desolvation technique, acquired suitable particle size of 177.67 ± 0.95 nm and entrapment efficiency of 98.7 ± 0.35% with perfectly uniform size distribution and high stability. Considering the attributes of the pulmonary route, NPs were co-spray dried with compatible carriers viz. mannitol, dextran, trehalose, leucine, glycine, aspartic acid, and glutamic acid to fabricate SDCMs. All formulations showed suitable mass median aerodynamic diameter<5 µm; that is suitable for deep lung deposition. However, the best aerosolization behavior was attained from using leucine with fine particle fraction (FPF) of 75.74%, followed by glycine with FPF of 54.7%. Finally, a pharmacodynamic study was conducted on bleomycin-induced mice, and it strongly revealed the role of the optimized formulations in alleviating PF through suppressing the levels of hydroxyproline, tumor necrosis factor-α and matrix metalloproteinase-9 with obvious improvements in the treated lung histopathology. These findings indicate that in addition to leucine, the glycine amino acid, which is not commonly used yet, is very promising in the formulation of DPIs.

Pyoderma Gangrenosum as a Harbinger of Adult T-Cell Leukemia-Lymphoma.

Adult T-cell leukemia-lymphoma (ATLL) is a malignancy of mature T lymphocytes caused by chronic human T-lymphotropic virus, type I (HTLV-I) infection. Up to one third of cases of ATLL can present with skin involvement-oftentimes there may only be skin involvement. Rare cutaneous presentations can further obscure the diagnosis, create diagnostic dilemma, and delay the institution of appropriate therapy. We present a case of ATLL where the initial lesion at presentation was pyoderma gangrenosum (PG). To our knowledge, there are no reported cases of ATLL presenting as PG.

Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers.

INTRODUCTION: Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms. METHODS: Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom. RESULTS: In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. CONCLUSION: MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.

Arachnoid Cyst: A Sudden Deterioration.

Arachnoid cysts are relatively rare and usually asymptomatic. It can only be diagnosed through radiological imaging modalities. Some patients may develop symptoms such as seizures, headache, dizziness, or psychiatric symptoms. We present a case of a 25-year-old male, previously healthy, who presented with sudden, repetitive episodes of seizure without regaining his consciousness. Computed tomography (CT) head scan showed a large cystic lesion that showed a rightward midline shift. Treatment was done surgically via endoscopic fenestration, and the patient remained symptom-free for one year. Most arachnoid cysts tend to remain asymptomatic throughout a patient's life span, allowing them to lead everyday normal lives; however, when these symptoms surface, they tend to be of a sudden nature requiring urgent surgical intervention. Our report follows the case of a young patient whose symptoms appear suddenly with triggers that led to status epilepticus. Our patient continued to suffer from multiple seizure attacks despite being on multiple anti-convulsive medications, and his symptoms eventually subsided via surgical intervention.

Effects of home healthcare for adults with chronic respiratory diseases and post-COVID-19 syndrome on hospital bed turnover rate: a protocol of systematic review with meta-analysis.

INTRODUCTION: Chronic respiratory diseases (CRDs) have a high prevalence, morbidity and mortality worldwide. After the COVID-19 pandemic, the number of patients readmitted after hospital discharge increased. For some populations, early hospital discharge and home healthcare may reduce health costs in patients treated at home when compared with those hospitalised. This study aims to systematically review the effectiveness of home healthcare for patients with CRDs and post-COVID-19 syndrome. METHODS AND ANALYSIS: We will search on MEDLINE, CENTRAL, Embase and PsycINFO. We will include randomised controlled trials (RCTs) and non-RCT studies reported in full text and abstracts. No language restriction will be applied. We will include studies related to adults with a diagnosis of CRDs or post-COVID-19 syndrome that compared in-patient hospital care with any home healthcare. We will exclude studies with participants with neurological, mental diseases, cancer or pregnant women. Two review authors will screen abstracts and select the eligible studies. To investigate the risk of bias, we will use the Cochrane 'Risk of Bias' tool for RCT, and the Risk of Bias In Non-randomised Studies-of Interventions for non-RCT. We will use the five Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) considerations to assess the quality of the evidence. Patients and the public will be involved in the preparation, execution and implementation phases of the review. ETHICS AND DISSEMINATION: No ethical approval is required because only published data will be analysed. The publication of the results in peer-reviewed journals and at relevant conferences will guide the direction of future research in the field and healthcare practice. The results will also be disseminated in plain language on social media to disseminate the knowledge to society and the public interested in the topic.

Application of simultaneous uncertainty quantification for image segmentation with probabilistic deep learning: Performance benchmarking of oropharyngeal cancer target delineation as a use-case.

Background: Oropharyngeal cancer (OPC) is a widespread disease, with radiotherapy being a core treatment modality. Manual segmentation of the primary gross tumor volume (GTVp) is currently employed for OPC radiotherapy planning, but is subject to significant interobserver variability. Deep learning (DL) approaches have shown promise in automating GTVp segmentation, but comparative (auto)confidence metrics of these models predictions has not been well-explored. Quantifying instance-specific DL model uncertainty is crucial to improving clinician trust and facilitating broad clinical implementation. Therefore, in this study, probabilistic DL models for GTVp auto-segmentation were developed using large-scale PET/CT datasets, and various uncertainty auto-estimation methods were systematically investigated and benchmarked. Methods: We utilized the publicly available 2021 HECKTOR Challenge training dataset with 224 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations as a development set. A separate set of 67 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations was used for external validation. Two approximate Bayesian deep learning methods, the MC Dropout Ensemble and Deep Ensemble, both with five submodels, were evaluated for GTVp segmentation and uncertainty performance. The segmentation performance was evaluated using the volumetric Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance at 95% (95HD). The uncertainty was evaluated using four measures from literature: coefficient of variation (CV), structure expected entropy, structure predictive entropy, and structure mutual information, and additionally with our novel Dice-risk measure. The utility of uncertainty information was evaluated with the accuracy of uncertainty-based segmentation performance prediction using the Accuracy vs Uncertainty (AvU) metric, and by examining the linear correlation between uncertainty estimates and DSC. In addition, batch-based and instance-based referral processes were examined, where the patients with high uncertainty were rejected from the set. In the batch referral process, the area under the referral curve with DSC (R-DSC AUC) was used for evaluation, whereas in the instance referral process, the DSC at various uncertainty thresholds were examined. Results: Both models behaved similarly in terms of the segmentation performance and uncertainty estimation. Specifically, the MC Dropout Ensemble had 0.776 DSC, 1.703 mm MSD, and 5.385 mm 95HD. The Deep Ensemble had 0.767 DSC, 1.717 mm MSD, and 5.477 mm 95HD. The uncertainty measure with the highest DSC correlation was structure predictive entropy with correlation coefficients of 0.699 and 0.692 for the MC Dropout Ensemble and the Deep Ensemble, respectively. The highest AvU value was 0.866 for both models. The best performing uncertainty measure for both models was the CV which had R-DSC AUC of 0.783 and 0.782 for the MC Dropout Ensemble and Deep Ensemble, respectively. With referring patients based on uncertainty thresholds from 0.85 validation DSC for all uncertainty measures, on average the DSC improved from the full dataset by 4.7% and 5.0% while referring 21.8% and 22% patients for MC Dropout Ensemble and Deep Ensemble, respectively. Conclusion: We found that many of the investigated methods provide overall similar but distinct utility in terms of predicting segmentation quality and referral performance. These findings are a critical first-step towards more widespread implementation of uncertainty quantification in OPC GTVp segmentation.