Contribution of Food from Market Purchases and Home Production to Child Nutrient Intake: Evidence from the EFFECTS Study Baseline Data.

BACKGROUND: Child undernutrition is prevalent in Tanzania, and households rely primarily on local markets and home production as food sources. However, little is known about the contribution of food market purchases to nutrient intakes among children consuming complementary foods. OBJECTIVE: To quantify the relationships between diversity of foods purchased and produced by households and adequate child nutrient intake in Mara, Tanzania. METHODS: Cross-sectional baseline dietary and household food source data from the EFFECTS study (ClinicalTrials.gov: NCT03759821) were collected from mothers of 586 children aged 9-23 months clustered in 80 villages in Mara, Tanzania. We conducted mixed effects linear regressions to quantify the association between diversity of foods consumed at home, from market purchases and home production, and nutrient intake adequacy (based on 24-hour food recalls). RESULTS: Children had inadequate diets, with fewer than half of children consuming adequate amounts of vitamin A, vitamin B1 (thiamine), vitamin B2 (riboflavin), vitamin B9 (folate), calcium, iron, and zinc. Breastfeeding was associated with higher overall mean adequacy (b=0.15-0.19 across models, p<0.001). Diversity of foods purchased was positively associated with intake of vitamin B12 and calcium (both p<0.001); this effect was attenuated among breastfed children. Among non-breastfed children, production diversity was positively associated with vitamin A intake (b=0.04, p<0.05) but not with intake of other nutrients. CONCLUSIONS: Both household food purchase diversity and food production diversity were positively associated with children's nutrient intake in rural Mara, Tanzania. Nutrition programming should consider the role of food markets in addition to home food production to improve child diets. CLINICAL TRIAL REGISTRY NUMBER: NCT03759821, https://clinicaltrials.gov/study/NCT03759821.

Impact of sunitinib resistance on clear cell renal cell carcinoma therapeutic sensitivity in vitro.

Sunitinib resistance creates a major clinical challenge for the treatment of advanced clear cell renal cell carcinoma (ccRCC) and functional and metabolic changes linked to sunitinib resistance are not fully understood. We sought to characterize the molecular and metabolic changes induced by the development of sunitinib resistance in ccRCC by developing and characterizing two human ccRCC cell lines resistant to sunitinib. Consistent with the literature, sunitinib-resistant ccRCC cell lines presented an aberrant overexpression of Axl and PD-L1, as well as a metabolic rewiring characterized by enhanced OXPHOS and glutamine metabolism. Therapeutic challenges of sunitinib-resistant ccRCC cell lines in vitro using small molecule inhibitors targeting Axl, AMPK and p38, as well as using PD-L1 blocking therapeutic antibodies, showed limited CTL-mediated cytotoxicity in a co-culture model. However, the AMPK activator metformin appears to sensitize the effect of PD-L1 blocking therapeutic antibodies and to enhance CTLs' cytotoxic effects on ccRCC cells. These effects were not broadly observed with the Axl and the p38 inhibitors. Taken together, these data suggest that targeting certain pathways aberrantly activated by sunitinib resistance such as the AMPK/PDL1 axis might sensitize ccRCC to immunotherapies as a second-line therapeutic approach.

Anthropogenic impacts on urban blue space and its reciprocal effect on human and socio-ecological health.

Quantifying anthropogenic impacts on blue space (BS) and its effect on human and socio-ecological health was least explored. The present study aimed to do this in reference to the urban BS transformation scenario of Eastern India. To measure BS transformation, Landsat image-based water indices were run from 1990 to 2021. Anthropogenic impact score (AIS) and 7 components scores of 78 selected BS on 70 parameters related data driven from the field. Total 345 respondents were taken for human and socio-ecological health assessment. For this, depression (DEP), anxiety (ANX), stress (STR), physical activities (PA), social capital (SC), therapeutic landscape (TL) and environment building (EB) parameters were taken. The result exhibited that BS was reduced. About 50% of urban core BS was reported highly impacted. Human and socio-ecological health was identified as good in proximity to BS, but it was observed better in the cases of larger peripheral BS. AIS on BS was found to be positively associated with mental health (0.47-0.63) and negatively associated with PA, SC, TL and EB (-0.50 to -0.90). Standard residual in ordinary least square was reported low (-1.5 to 1.5) in 95% BS. Therefore, BS health restoration and management is crucial for sustaining the living environment.

ComplexEye: a multi-lens array microscope for high-throughput embedded immune cell migration analysis.

Autonomous migration is essential for the function of immune cells such as neutrophils and plays an important role in numerous diseases. The ability to routinely measure or target it would offer a wealth of clinical applications. Video microscopy of live cells is ideal for migration analysis, but cannot be performed at sufficiently high-throughput (HT). Here we introduce ComplexEye, an array microscope with 16 independent aberration-corrected glass lenses spaced at the pitch of a 96-well plate to produce high-resolution movies of migrating cells. With the system, we enable HT migration analysis of immune cells in 96- and 384-well plates with very energy-efficient performance. We demonstrate that the system can measure multiple clinical samples simultaneously. Furthermore, we screen 1000 compounds and identify 17 modifiers of migration in human neutrophils in just 4 days, a task that requires 60-times longer with a conventional video microscope. ComplexEye thus opens the field of phenotypic HT migration screens and enables routine migration analysis for the clinical setting.

Integrated Meta-Omics Analysis Unveils the Pathways Modulating Tumorigenesis and Proliferation in High-Grade Meningioma.

Meningioma, a primary brain tumor, is commonly encountered and accounts for 39% of overall CNS tumors. Despite significant progress in clinical research, conventional surgical and clinical interventions remain the primary treatment options for meningioma. Several proteomics and transcriptomics studies have identified potential markers and altered biological pathways; however, comprehensive exploration and data integration can help to achieve an in-depth understanding of the altered pathobiology. This study applied integrated meta-analysis strategies to proteomic and transcriptomic datasets comprising 48 tissue samples, identifying around 1832 common genes/proteins to explore the underlying mechanism in high-grade meningioma tumorigenesis. The in silico pathway analysis indicated the roles of extracellular matrix organization (EMO) and integrin binding cascades in regulating the apoptosis, angiogenesis, and proliferation responsible for the pathobiology. Subsequently, the expression of pathway components was validated in an independent cohort of 32 fresh frozen tissue samples using multiple reaction monitoring (MRM), confirming their expression in high-grade meningioma. Furthermore, proteome-level changes in EMO and integrin cell surface interactions were investigated in a high-grade meningioma (IOMM-Lee) cell line by inhibiting integrin-linked kinase (ILK). Inhibition of ILK by administrating Cpd22 demonstrated an anti-proliferative effect, inducing apoptosis and downregulating proteins associated with proliferation and metastasis, which provides mechanistic insight into the disease pathophysiology.

Vincristine Enhances the Efficacy of MEK Inhibitors in Preclinical Models of KRAS-mutant Colorectal Cancer.

Mutations in KRAS are found in more than 50% of tumors from patients with metastatic colorectal cancer (mCRC). However, direct targeting of most KRAS mutations is difficult; even the recently developed KRASG12C inhibitors failed to show significant benefit in patients with mCRC. Single agents targeting mitogen-activated protein kinase kinase (MEK), a downstream mediator of RAS, have also been ineffective in colorectal cancer. To identify drugs that can enhance the efficacy of MEK inhibitors, we performed unbiased high-throughput screening using colorectal cancer spheroids. We used trametinib as the anchor drug and examined combinations of trametinib with the NCI-approved Oncology Library version 5. The initial screen, and following focused validation screens, identified vincristine as being strongly synergistic with trametinib. In vitro, the combination strongly inhibited cell growth, reduced clonogenic survival, and enhanced apoptosis compared with monotherapies in multiple KRAS-mutant colorectal cancer cell lines. Furthermore, this combination significantly inhibited tumor growth, reduced cell proliferation, and increased apoptosis in multiple KRAS-mutant patient-derived xenograft mouse models. In vivo studies using drug doses that reflect clinically achievable doses demonstrated that the combination was well tolerated by mice. We further determined that the mechanism underlying the synergistic effect of the combination was due to enhanced intracellular accumulation of vincristine associated with MEK inhibition. The combination also significantly decreased p-mTOR levels in vitro, indicating that it inhibits both RAS-RAF-MEK and PI3K-AKT-mTOR survival pathways. Our data thus provide strong evidence that the combination of trametinib and vincristine represents a novel therapeutic option to be studied in clinical trials for patients with KRAS-mutant mCRC. SIGNIFICANCE: Our unbiased preclinical studies have identified vincristine as an effective combination partner for the MEK inhibitor trametinib and provide a novel therapeutic option to be studied in patients with KRAS-mutant colorectal cancer.

Factors influencing and changes in childhood vaccination coverage over time in Bangladesh: a multilevel mixed-effects analysis.

INTRODUCTION: This study aimed to investigate the associated factors and changes in childhood vaccination coverage over time in Bangladesh. METHODS: Bangladesh's Demographic and Health Surveys from 2011, 2014, and 2017-18 provided data for this study on vaccination coverage among children aged 12 to 35 months. For three survey periods, multilevel binary logistic regression models were employed. RESULTS: The overall prevalence (weighted) of full vaccination among children aged 12-35 months were 86.17% in 2011, 85.13% in 2014, and 89.23% in 2017-18. Children from families with high wealth index, mothers with higher education, and over the age of 24 and who sought at least four ANC visits, as well as children from urban areas were more likely to receive full vaccination. Rangpur division had the highest change rate of vaccination coverage from 2011 to 2014 (2.26%), whereas Sylhet division had the highest change rate from 2014 to 2017-18 (34.34%). CONCLUSION: To improve immunization coverage for Bangladeshi children, policymakers must integrate vaccine programs, paying special attention to mothers without at least a high school education and families with low wealth index. Increased antenatal care visits may also aid in increasing the immunization coverage of their children.

Classifying histopathological images of oral squamous cell carcinoma using deep transfer learning.

Oral cancer is a prevalent malignancy that affects the oral cavity in the region of head and neck. The study of oral malignant lesions is an essential step for the clinicians to provide a better treatment plan at an early stage for oral cancer. Deep learning based computer-aided diagnostic system has achieved success in many applications and can provide an accurate and timely diagnosis of oral malignant lesions. In biomedical image classification, getting large training dataset is a challenge, which can be efficiently handled by transfer learning as it retrieves the general features from a dataset of natural images and adapted directly to new image dataset. In this work, to achieve an effective deep learning based computer-aided system, the classifications of Oral Squamous Cell Carcinoma (OSCC) histopathology images are performed using two proposed approaches. In the first approach, to identify the best appropriate model to differentiate between benign and malignant cancers, transfer learning assisted deep convolutional neural networks (DCNNs), are considered. To handle the challenge of small dataset and further increase the training efficiency of the proposed model, the pretrained VGG16, VGG19, ResNet50, InceptionV3, and MobileNet, are fine-tuned by training half of the layers and leaving others frozen. In the second approach, a baseline DCNN architecture, trained from scratch with 10 convolution layers is proposed. In addition, a comparative analysis of these models is carried out in terms of classification accuracy and other performance measures. The experimental results demonstrate that ResNet50 obtains substantially superior performance than selected fine-tuned DCNN models as well as the proposed baseline model with an accuracy of 96.6%, precision and recall values are 97% and 96%, respectively.

Protocol to Assess the Biological Activity of Insulin Glargine, Insulin Lispro, and Insulin Aspart In Vitro.

Insulin is a hormone produced by ß-cells of the pancreas and controls the amount of sugar in the blood. Since its discovery over 100 years ago, insulin has been used as a life-saving treatment for people with diabetes. Historically, the biological activity or bioidentity of insulin products has been assessed using an in vivo model. However, reduction in animal experiments is a goal for many worldwide, and there is a need to develop in vitro bioassays to reliably test the biological activity of insulin products. This article describes an in vitro cell-based method to assess the biological activity of insulin glargine, insulin aspart, and insulin lispro in a step-by-step manner.

Economic and socioecological perspectives of urban wetland loss and processes: a study from literatures.

Existing literatures across the world highlighted the causes and rate of wetland loss; however, so far, no researches tried to analyze how these are guided by the socioeconomic and ecological conditions. The current review work wished to explore how economic and socioecological perspectives could control the rate and drivers of urban wetland loss. Through meta-analysis, this study also intended to explore the changing polarity in research publication and collaborative research. Total 287 original research articles indicating the rates and drivers of wetland loss from 1990 to June 2022 for the first objective and 1500 articles focusing wetland researches from Dimensions AI database for the last objective were taken.Results clearly revealed that the rate of urban wetland loss varies from 0.03 to 3.13% annually, and three main drivers like built-up, agricultural expansions, pollution were identified all across the world. Loss rate was found maximum in the developing and least developed countries. Pollution, built-up expansion, and agriculture expansion, respectively, in developed, developing, and least developed nations were identified as the most dominant drivers of urban wetland loss. Linking loss rate and drivers with socioecological and economic perspectives revealed that human development index (HDI), ecological performance index (EPI), sustainable development goal index (SDGI), and social progress index (SPI) is negatively associated with the rate of urban wetland loss. Contrarily, a poverty rate encouraged higher rate of loss. This study articulated that improving these socioecological and economic conditions could help wetland conservation and restoration to achieve SDGs.

Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks.

The COVID-19 pandemic has put a huge challenge on the Indian health infrastructure. With a larger number of people getting affected during the second wave, hospitals were overburdened, running out of supplies and oxygen. Hence, predicting new COVID-19 cases, new deaths, and total active cases multiple days in advance can aid better utilization of scarce medical resources and prudent pandemic-related decision-making. The proposed method uses gated recurrent unit networks as the main predicting model. A study is conducted by building four models pre-trained on COVID-19 data from four different countries (United States of America, Brazil, Spain, and Bangladesh) and fine-tuned on India's data. Since the four countries chosen have experienced different types of infection curves, the pre-training provides a transfer learning to the models incorporating diverse situations into account. Each of the four models then gives 7-day ahead predictions using the recursive learning method for the Indian test data. The final prediction comes from an ensemble of the predictions of the different models. This method with two countries, Spain and Bangladesh, is seen to achieve the best performance amongst all the combinations as well as compared to other traditional regression models.

Combining MEK and SRC inhibitors for treatment of colorectal cancer demonstrate increased efficacy in vitro but not in vivo.

Metastatic colorectal cancer (mCRC) is the second leading cause of cancer deaths in the United States. More than 50% of patients with mCRC harbor mutations of the oncogenic driver RAS (KRAS or NRAS). Because directly targeting most mutations of RAS is technically challenging, researchers have concentrated on targeting MEK, a downstream mediator of RAS. However, targeting MEK as single-agent therapy is ineffective in patients with mCRC. We hypothesize that combining a MEK inhibitor with other agents can enhance the efficacy of MEK targeting in mCRC. Unbiased high-throughput screening (HTS) was performed to identify drugs that enhance the efficacy of MEK inhibitors. HTS was performed with KRAS-mutated CRC cells using the MEK inhibitor trametinib as a "backbone" and two "clinically ready" compound libraries approved by the U.S. Food and Drug Administration or in clinical trials. HTS demonstrated that the combination of the SRC inhibitor dasatinib and trametinib was synergistic in CRC cells in vitro (MTT and colony formation assays). Analysis of markers for cell proliferation and apoptosis using fluorescence-activated cell sorting, reverse-phase protein array, or Western blotting demonstrated decreased cell proliferation and increased cell death when targeting both SRC and MEK as compared to single agents in multiple CRC cell lines. However, combining dasatinib and trametinib in vivo at doses in mice equivalent to doses used in humans failed to significantly enhance the antitumor activity of trametinib when compared to that of trametinib alone. These results underscore the importance of performing careful preclinical in vivo validation studies using clinically relevant doses as a prerequisite for translating in vitro findings to the clinic.

CO RADS grade of HRCT Thorax and RT PCR testing for the diagnosis of coronavirus disease 2019 (COVID 19): A descriptive hospital based study of asymptomatic planned surgery cases.

Background: The coronavirus disease 2019 (COVID-19) reporting and data system (CO-RADS) grade of high-resolution computed tomography (HRCT)-thorax scan investigation is an innovative tool for the diagnosis of COVID-19 patients. By this tool, majority of moderate-to-severe COVID-19 patients are screened to detect lung pathologies. Hardly any study has explored its use vis-a-vis reverse transcriptase-polymerase chain reaction (RT-PCR) in asymptomatic patients. Objectives: (1) The objective of the study is to assess the frequency COVID-19 patients among asymptomatic subjects who were admitted in the hospital for planned surgery, (2) estimate the sensitivity and specificity of CO-RADS grade of HRCT-thorax investigation for the diagnosis of COVID-19 patients where RT-PCR test was considered as "Gold Standard" test. Methodology: A descriptive retrospective study was conducted by studying the records in the case files of 150 patients who were admitted in the Department of General Surgery, Man Mohini Health Clinic, Murshidabad, West Bengal for minor surgical procedures between September 1 and December 31, 2020. Data were collected from hospital records. The CO-RADS grade of HRCT-thorax investigation and RT-PCR test were performed for the diagnosis of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) virus. The MS-excel application was applied for data analysis. Results: The mean age of the participants was 42.58 ± 14.29 years. A total of 17 (11%) and 39 (26%) of the patients were diagnosed with COVID-19 by HRCT-thorax and RT-PCR test, respectively. The sensitivity and specificity of CO-RADS grade of HRCT-thorax investigation for diagnosis of COVID-19 patients were 43.58% and 100%, respectively. The positive and negative predictive values of CO-RADS grade of HRCT-thorax investigation were 100% and 83.45%, respectively. Conclusions: The frequency of asymptomatic patients with COVID-19 that was missed by HRCT thorax was high, compared to the gold standard RT-PCR, reflecting its low sensitivity and low negative predictive value in the diagnosis of SARS-CoV-2 virus infection. Hence, it is difficult to conclude in favor of HRCT thorax as first-line screening modality in all individuals.

Résumé Contexte: Le système de notification et de données sur la maladie à coronavirus 2019 (COVID 19) (CO RADS) la tomographie (HRCT)­exploration du thorax est un outil innovant pour le diagnostic des patients COVID 19. Par cet outil, la majorité des Les patients COVID 19 modérés à sévères sont dépistés pour détecter les pathologies pulmonaires. Pratiquement aucune étude n'a exploré son utilisation vis-à-vis réaction en chaîne par transcriptase polymérase (RT PCR) chez des patients asymptomatiques. Objectifs: (1) L'objectif de l'étude est d'évaluer la fréquence Patients COVID 19 parmi les sujets asymptomatiques qui ont été admis à l'hôpital pour une chirurgie planifiée, (2) estimer la sensibilité et la spécificité de grade CO-RADS de l'investigation HRCT-thorax pour le diagnostic des patients COVID-19 où le test RT-PCR a été considéré comme "Gold Standard" test. Méthodologie: Une étude rétrospective descriptive a été menée en étudiant les dossiers des dossiers de 150 patients admis dans le département de chirurgie générale, clinique de santé Man Mohini, Murshidabad, Bengale occidental pour des interventions chirurgicales mineures entre septembre 1 et 31 décembre 2020. Les données ont été recueillies à partir des dossiers hospitaliers. Le grade CO RADS de l'examen HRCT thorax et du test RT PCR était réalisée pour le diagnostic du virus du coronavirus 2 lié au syndrome respiratoire aigu sévère (SRAS CoV 2). L'application MS Excel a été appliquée pour l'analyse des données. Résultats: L'âge moyen des participants était de 42,58 ± 14,29 ans. Au total, 17 (11 %) et 39 (26 %) des patients ont été diagnostiqués avec COVID 19 par HRCT thorax et test RT PCR, respectivement. La sensibilité et la spécificité du grade CO-RADS de l'investigation HRCT-thorax pour le diagnostic des patients COVID-19 étaient de 43,58 % et 100 %, respectivement. Les valeurs prédictives positives et négatives du grade CO RADS de L'investigation HRCT-thorax était de 100 % et 83,45 %, respectivement. Conclusions: La fréquence des patients asymptomatiques atteints de COVID 19 qui manqué par HRCT thorax était élevé, par rapport à la RT-PCR de référence, reflétant sa faible sensibilité et sa faible valeur prédictive négative dans le diagnostic d'infection par le virus SARS CoV 2. Par conséquent, il est difficile de conclure en faveur de HRCT thorax comme modalité de dépistage de première ligne chez tous les individus. Mots-clés: personnes asymptomatiques, tomodensitométrie haute résolution - thorax, transcriptase inverse-réaction en chaîne par polymérase maladie à coronavirus 2019.

A mouse pancreatic organoid model to compare PD-L1 blocking antibodies.

Immune checkpoint inhibitors (ICIs) have changed the therapeutic landscape for cancer patients, but diabetes, a rare, severe immune-related endocrinopathy, is linked to ICI therapy. It is unclear whether glycosylation of ICIs may play a role in the development of this adverse event and how the physiological effects of different ICIs on pancreatic cells should be evaluated. We used a mouse pancreatic organoid model to compare three PD-L1 blocking antibodies in the presence or absence of IFNγ using a metabolic bioanalyzer. Modulation of ICI glycosylation altered its metabolic effects on mouse pancreatic organoids, suggesting that this model could be used to monitor and compare ICIs and to study the mechanisms underlying the development of IC-mediated diabetes.

A Review on Bioinks and their Application in Plant Bioprinting.

In recent years, the characterization and fabrication methods concerning new bioinks have received much attention, largely because the absence of bioprintable materials has been identified as one of the most rudimentary challenges for rapid advancement in the field of three-dimensional (3D) printing. Bioinks for printing mammalian organs have been rapidly produced, but bioinks in the field of plant science remain sparse. Thus, 3D fabrication of plant parts is still in its infancy due to the lack of appropriate bioink materials, and aside from that, the difficulty in recreating sophisticated microarchitectures that accurately and safely mimic natural biological activities is a concern. Therefore, this review article is designed to emphasize the significance of bioinks and their applications in plant bioprinting.

Linking Depressive and Anxiety Symptoms with Diet Quality of University Students: A Cross-Sectional Study during the COVID-19 Pandemic in India.

This study examines the association of depressive and anxiety symptoms with diet quality among university students while controlling for different demographic and other health and lifestyle factors. This cross-sectional study was carried out between April 2021 and June 2021 among a total of 440 (unweighted) university students. Diet quality was assessed using a 10-item mini-dietary assessment index tool. The depressive and anxiety symptoms of participants were measured using the validated Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder (GAD-7) scale, respectively. Multivariable logistic regression and mediation analyses were performed. In this study, 61.1% (95% CI: 56.6% to 65.7%) of university students' diet quality was good during the COVID-19 pandemic. Being a post-graduate student, an urban resident, having no depressive (AOR = 2.15, 95% CI: 1.20 to 3.84) and anxiety symptoms (AOR = 1.96, 95% CI: 1.07 to 3.59), no changes or improvement in appetite, and no changes in sleep duration were significantly associated with good diet quality among our study participants. Depressive and anxiety symptoms during COVID-19 had a significant effect on the diet quality of university students. Future public health policies need to be focused on improving the mental health and well-being of students particularly during pandemic situations to enhance their diet quality.

Riboflavin salvage by Borrelia burgdorferi supports carbon metabolism and is essential for survival in the tick vector.

The Lyme disease agent, Borrelia burgdorferi, harbors a significantly reduced genome and relies on the scavenging of critical nutrients from its tick and mammalian hosts for survival. Riboflavin salvage has been shown to be important for B. burgdorferi infection of mice, yet the contributions of riboflavin to B. burgdorferi metabolism and survival in the tick remain unknown. Using a targeted mass spectrometry approach, we confirmed the importance of bb0318, the putative ATPase component of an ABC-type riboflavin transporter, for riboflavin salvage and the production of FMN and FAD. This analysis further revealed that Δbb0318 B. burgdorferi displayed increased levels of glycerol 3-phosphate compared to the wild-type. The glycerol 3-phosphate dehydrogenase activity of GlpD was found to be FAD-dependent and the transcription and translation of glpD were significantly decreased in Δbb0318 B. burgdorferi. Finally, gene bb0318 was found to be important for maximal spirochete burden in unfed larvae and essential for survival in feeding ticks. Together, these data demonstrate the importance of riboflavin salvage for B. burgdorferi carbon metabolism and survival in ticks.

Nature's palette: An emerging frontier for coloring dairy products.

Consumers all across the world are looking for the most delectable and appealing foods, while also demanding products that are safer, more nutritious, and healthier. Substitution of synthetic colorants with natural colorants has piqued consumer and market interest in recent years. Due to increasing demand, extensive research has been conducted to find natural and safe food additives, such as natural pigments, that may have health benefits. Natural colorants are made up of a variety of pigments, many of which have significant biological potential. Because of the promising health advantages, natural colorants are gaining immense interest in the dairy industry. This review goes over the use of various natural colorants in dairy products which can provide desirable color as well as positive health impacts. The purpose of this review is to provide an in-depth look into the field of food (natural or synthetic) colorants applied in dairy products as well as their potential health benefits, safety, general trends, and future prospects in food science and technology. In this paper, we listed a plethora of applications of natural colorants in various milk-based products.

Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples.

Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.

PD-L1 Mediates IFNγ-Regulation of Glucose but Not of Tryptophan Metabolism in Clear Cell Renal Cell Carcinoma.

The immune checkpoint programmed death-ligand 1 (PD-L1) is expressed on the cell surface of tumor cells and is key for maintaining an immunosuppressive microenvironment through its interaction with the programmed death 1 (PD-1). Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic cancer characterized by an aberrant aerobic glycolytic metabolism and is known to overexpress PD-L1. Multiple immunotherapies have been approved for the treatment of ccRCC, including cytokines and immune checkpoint inhibitors. Recently the intrinsic role of PD-L1 and interferon gamma (IFNγ) signaling have been studied in several types of tumor cells, yet it remains unclear how they affect the metabolism and signaling pathways of ccRCC. Using metabolomics, metabolic assays and RNAseq, we showed that IFNγ enhanced aerobic glycolysis and tryptophan metabolism in ccRCC cells in vitro and induced the transcriptional expression of signaling pathways related to inflammation, cell proliferation and cellular energetics. These metabolic and transcriptional effects were partially reversed following transient PD-L1 silencing. Aerobic glycolysis, as well as signaling pathways related to inflammation, were not induced by IFNγ when PD-L1 was silenced, however, tryptophan metabolism and activation of Jak2 and STAT1 were maintained. Our data demonstrate that PD-L1 expression is required to mediate some of IFNγ's effect in ccRCC cells and highlight the importance of PD-L1 signaling in regulating the metabolism of ccRCC cells in response to inflammatory signals.