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Multidrug resistance (MDR) of cancer cells remains a major obstacle to favorable outcomes of treatment with many drugs, including doxorubicin. Most of the clinical trials failed to demonstrate the benefit of the drug efflux transporter P-glycoprotein (P-gp) inhibitors to circumvent P-gp-mediated drug resistance in vivo. The present study explored the therapeutic potential of combined treatment with liposomal doxorubicin, P-gp inhibitor quinine, and the photodynamic therapy (PDT) using indocyanine green (ICG) in the adenocarcinoma drug-resistant tumor model. Liposomes were actively co-remotely loaded with doxorubicin and quinine, and ICG was passively adsorbed. The liposomes were characterized by differential scanning calorimetry (DSC) and cryogenic transmission microscopy (Cryo-TEM). We found that quinine impaired the crystalline structure of doxorubicin. In vitro, treatment with single agents themselves was insufficient to inhibit the growth of HT-29 MDR1 cells. However, pegylated liposomal doxorubicin and quinine (PLDQ) significantly diminished HT-29 MDR1 cell survival. Furthermore, survival inhibition intensified by the addition of ICG to the PLDQ (ICG + PLDQ). In vivo, ICG + PLDQ significantly decreased tumor growth when combined with tumor irradiation with NIR light (** p < 0.01). ICG + PLDQ + irradiation was superior to single treatments or combinational treatments without irradiation. These findings suggest that ICG + PLDQ can overcome P-gp-mediated MDR in cancer cells.

The multidrug resistance protein 1 (MDR1; P-glycoprotein) has been associated with efflux of chemotherapeutic agents from tumor cells and with poor patient prognosis. This study evaluated the feasibility of non-invasive, non-radioactive near infrared (NIR) imaging methodology for detection of MDR1 functional activity in tumors. Initial accumulation assays were conducted in MDR1-overexpressing MDCK cells (MDCK-MDR1) and control MDCK cells (MDCK-CT) using the NIR dyes indocyanine green (ICG), IR-783, IR-775, rhodamine 800, XenoLight DiR, and Genhance 750, at 0.4 μM-100 μM. ICG and IR-783 were also evaluated in HT-29 cells in which MDR1 overexpression was induced by colchicine (HT-29-MDR1) and their controls (HT-29-CT). optical imaging studies were conducted using immunodeficient mice bearing HT-29-CT and HT-29-MDR1 xenografts. ICG's emission intensity was 2.0- and 2.2-fold higher in control versus MDR1-overexpressing cells, in MDCK and HT-29 cell lines, respectively. The respective IR-783 control:MDR1 ratio was 1.4 in both MDCK and HT-29 cells. Optical imaging of mice bearing HT-29-CT and HT-29-MDR1 xenografts revealed a statistically non-significant, 1.7-fold difference ( > 0.05) in ICG emission intensity between control and MDR1 tumors. No such differences were observed with IR-783. ICG and IR-783 appear to be weak MDR1 substrates. , low sensitivity and high between-subject variability impair the ability to use the currently studied probes as markers of tumor MDR1 activity. The results suggest that, for future use of this technology, additional NIR probes should be screened as MDR1 substrates.

When speaking to infants, adults often produce speech that differs systematically from that directed to other adults. To quantify the acoustic properties of this speech style across a wide variety of languages and cultures, we extracted results from empirical studies on the acoustic features of infant-directed speech. We analysed data from 88 unique studies (734 effect sizes) on the following five acoustic parameters that have been systematically examined in the literature: fundamental frequency ( f 0 ), f 0 variability, vowel space area, articulation rate and vowel duration. Moderator analyses were conducted in hierarchical Bayesian robust regression models to examine how these features change with infant age and differ across languages, experimental tasks and recording environments. The moderator analyses indicated that f 0 , articulation rate and vowel duration became more similar to adult-directed speech over time, whereas f 0 variability and vowel space area exhibited stability throughout development. These results point the way for future research to disentangle different accounts of the functions and learnability of infant-directed speech by conducting theory-driven comparisons among different languages and using computational models to formulate testable predictions. This meta-analysis examines different features of infant-directed speech across languages and infant ages. The results suggest that there are cross-linguistic tendencies and that caregivers adjust the properties of infant-directed speech to suit infants’ changing needs.

Background In recent years, several large studies have assessed the costs of national infant immunization programs, and the results of these studies are used to support planning and budgeting in low- and middle-income countries. However, few studies have addressed the costs and cost-effectiveness of interventions to improve immunization coverage, despite this being a major focus of policy attention. Without this information, countries and international stakeholders have little objective evidence on the efficiency of competing interventions for improving coverage. Methods We conducted a systematic literature review on the costs and cost-effectiveness of interventions to improve immunization coverage in low- and middle-income countries, including both published and unpublished reports. We evaluated the quality of included studies and extracted data on costs and incremental coverage. Where possible, we calculated incremental cost-effectiveness ratios (ICERs) to describe the efficiency of each intervention in increasing coverage. Results A total of 14 out of 41 full text articles reviewed met criteria for inclusion in the final review. Interventions for increasing immunization coverage included demand generation, modified delivery approaches, cash transfer programs, health systems strengthening, and novel technology usage. We observed substantial heterogeneity in costing methods and incompleteness of cost and coverage reporting. Most studies reported increases in coverage following the interventions, with coverage increasing by an average of 23 percentage points post-intervention across studies. ICERs ranged from $0.66 to $161.95 per child vaccinated in 2017 USD. We did not conduct a meta-analysis given the small number of estimates and variety of interventions included. Conclusions There is little quantitative evidence on the costs and cost-effectiveness of interventions for improving immunization coverage, despite this being a major objective for national immunization programs. Efforts to improve the level of costing evidence—such as by integrating cost analysis within implementation studies and trials of immunization scale up—could allow programs to better allocate resources for coverage improvement. Greater adoption of standardized cost reporting methods would also enable the synthesis and use of cost data.

Background To plan for the financial sustainability of immunization programs and make informed decisions to improve immunization coverage and equity, decision-makers need to know how much these programs cost beyond the cost of the vaccine. Non-vaccine delivery cost estimates can significantly influence the cost-effectiveness estimates used to allocate resources at the country level. However, many low- and middle-income countries (LMICs) do not have immunization delivery unit cost estimates available, or have estimates that are uncertain, unreliable, or old. We undertook a Bayesian evidence synthesis to generate country-level estimates of immunization delivery unit costs for LMICs. Methods From a database of empirical immunization costing studies, we extracted estimates of the delivery cost per dose for routine childhood immunization services, excluding vaccine costs. A Bayesian meta-regression model was used to regress delivery cost per dose estimates, stratified by cost category, against a set of predictor variables including country-level [gross domestic product per capita, reported diphtheria-tetanus-pertussis third dose coverage (DTP3), population, and number of doses in the routine vaccination schedule] and study-level (study year, single antigen or programmatic cost per dose, and financial or economic cost) predictors. The fitted prediction model was used to generate standardized estimates of the routine immunization delivery cost per dose for each LMIC for 2009–2018. Alternative regression models were specified in sensitivity analyses. Results We estimated the prediction model using the results from 29 individual studies, covering 24 countries. The predicted economic cost per dose for routine delivery of childhood vaccines (2018 US dollars), not including the price of the vaccine, was $1.87 (95% uncertainty interval $0.64–4.38) across all LMICs. By individual cost category, the programmatic economic cost per dose for routine delivery of childhood vaccines was $0.74 ($0.26–1.70) for labor, $0.26 ($0.08–0.67) for supply chain, $0.22 ($0.06–0.57) for capital, and $0.65 ($0.20–1.66) for other service delivery costs. Conclusions Accurate immunization delivery costs are necessary for assessing the cost-effectiveness and strategic planning needs of immunization programs. The cost estimates from this analysis provide a broad indication of immunization delivery costs that may be useful when accurate local data are unavailable.

High levels of urea in blood, milk and urine have been linked to poor nitrogen efficiency, increased feed costs, poor reproductive performance and increased environmental impacts of dairy farming. Milk urea nitrogen (MUN) is a commonly used metric to manage herd nitrogen efficiency, with current recommendations for MUN to be between 8–14 mg/dL to maintain milk production and reduce nitrogen losses. However, a previous work suggests commercial analysis of MUN with mid-infrared spectroscopy (MIR) may not be precise enough to determine if a milk sample is within the recommended range. Thus, the objective of this study was to evaluate the precision and accuracy of milk testing lab MUN measurements. Four sets of bulk tank samples were sent to 3 commercial labs and one research lab for analysis by MIR. Samples were sent to commercial labs in duplicate and MUN was also assessed through an enzymatic assay. The Euclidean distance (ED) was calculated as a combined metric of precision and accuracy. The ED was not different between labs and ranged from 0.81–1.27. Repeatability (sr) and reproducibility (sR) were estimated for commercial labs and ranged from (0.297–0.469) and (0.555–0.791) respectively. Differences between individual sample MIR and enzymatic MUN were regressed on the centered enzymatic MUN in a linear mixed model that included a random effect of lab and fixed effects for milk protein and milk fat. Regression results indicate MIR analysis over-predicts MUN at low MUN concentrations and under predicts MUN at high MUN concentrations. Results suggest MIR analysis of MUN is more accurate around milk MUN, protein, and fat concentrations of ~13 mg/dl, 3.4% protein, and 4.2% fat. Further, the combined residual error and random effect of lab suggest the standard error of an MUN MIR measurement is ±1.8.

High levels of urea in blood, milk and urine have been linked to poor nitrogen efficiency, increased feed costs, poor reproductive performance and increased environmental impacts of dairy farming. Milk urea nitrogen (MUN) is a commonly used metric to manage herd nitrogen efficiency, with current recommendations for MUN to be between 8-14 mg/dL to maintain milk production and reduce nitrogen losses. However, a previous work suggests commercial analysis of MUN with mid-infrared spectroscopy (MIR) may not be precise enough to determine if a milk sample is within the recommended range. Thus, the objective of this study was to evaluate the precision and accuracy of milk testing lab MUN measurements. Four sets of bulk tank samples were sent to 3 commercial labs and one research lab for analysis by MIR. Samples were sent to commercial labs in duplicate and MUN was also assessed through an enzymatic assay. The Euclidean distance (ED) was calculated as a combined metric of precision and accuracy. The ED was not different between labs and ranged from 0.81-1.27. Repeatability (sr) and reproducibility (sR) were estimated for commercial labs and ranged from (0.297-0.469) and (0.555-0.791) respectively. Differences between individual sample MIR and enzymatic MUN were regressed on the centered enzymatic MUN in a linear mixed model that included a random effect of lab and fixed effects for milk protein and milk fat. Regression results indicate MIR analysis over-predicts MUN at low MUN concentrations and under predicts MUN at high MUN concentrations. Results suggest MIR analysis of MUN is more accurate around milk MUN, protein, and fat concentrations of ~13 mg/dl, 3.4% protein, and 4.2% fat. Further, the combined residual error and random effect of lab suggest the standard error of an MUN MIR measurement is ±1.8.

Macrophages activate robust antimicrobial functions upon engulfing virulent bacteria, yet a wide array of pathogens paradoxically thrive within these innate immune cells. To probe the pathogen-macrophage interface, we used proteomics to comprehensively quantify changes in post-translational modifications (PTMs) of host proteins during infection with three evolutionarily diverse intracellular pathogens: Mycobacterium tuberculosis, Salmonella enterica serovar Typhimurium, and Listeria monocytogenes. Comparing global phosphorylation and ubiquitylation patterns identified extensive reprogramming of cellular pathways during infection, with ubiquitylation patterns revealing unique pathogen-specific molecular response signatures undetectable by transcriptional profiling. Differential PTM changes during infection with attenuated M. tuberculosis cells lacking the ESX-1 virulence determinant revealed extensive modification of phagosome dynamics and antiviral type I interferon activation. We found that M. tuberculosis-mediated activation of the antiviral OASL1-IRF7 pathway promotes bacterial replication, uncovering a new mechanism of virus-bacterial synergy. Our data reveals remarkable specificity in innate cellular responses to complex stimuli and provides a resource for deeper understanding of host-pathogen interactions.