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The impact of age on mesenchymal stromal cell (MSC) characteristics has been well researched. However, increased age is concomitant with increased prevalence of polypharmacy. This adjustable factor may have further implications for the functionality of MSCs and the effectiveness of autologous MSC procedures. We applied hyperspectral microscopy of cell autofluorescence—a non-invasive imaging technique used to characterise cytometabolic heterogeneity—to identify changes in the autofluorescence signals of MSCs from (1) young mice, (2) old mice, (3) young mice randomised to receive polypharmacy (9–10 weeks of oral therapeutic doses of simvastatin, metoprolol, oxycodone, oxybutynin and citalopram), and (4) old mice randomised to receive polypharmacy. Principal Component Analysis and Logistic Regression Analysis were used to assess alterations in spectral and associated metabolic characteristics. Modelling demonstrated that cells from young mice receiving polypharmacy had less NAD(P)H and increased porphyrin relative to cells from old control mice, allowing for effective separation of the two groups (AUC of ROC curve > 0.94). Similarly, cells from old polypharmacy mice were accurately separated from those from young controls due to lower levels of NAD(P)H (p < 0.001) and higher porphyrin (p < 0.001), allowing for an extremely accurate logistic regression (AUC of ROC curve = 0.99). This polypharmacy regimen may have a more profound impact on MSCs than ageing, and can simultaneously reduce optical redox ratio (ORR) and increase porphyrin levels. This has implications for the use of autologous MSCs for older patients with chronic disease.

Abstract Aging, polypharmacy (concurrent use of ≥ 5 medications), and functional impairment are global healthcare challenges. However, knowledge of the age/sex-specific effects of polypharmacy is limited, particularly on daily physical activities. Using continuous monitoring, we demonstrated how polypharmacy with high Drug Burden Index (DBI—cumulative anticholinergic/sedative exposure) affected behaviors over 23 h in male/female, young/old mice. For comparison, we also evaluated how different drug regimens (polypharmacy/monotherapy) influenced activities in young mice. We found that after 4 weeks of treatment, high DBI (HDBI) polypharmacy decreased exploration (reduced mean gait speed and climbing) during the habituation period, but increased it during other periods, particularly in old mice during the transition to inactivity. After HDBI polypharmacy, mean gait speed consistently decreased throughout the experiment. Some behavioral declines after HDBI were more marked in females than males, indicating treatment × sex interactions. Metoprolol and simvastatin monotherapies increased activities in young mice, compared to control/polypharmacy. These findings highlight that in mice, some polypharmacy-associated behavioral changes are greater in old age and females. The observed diurnal behavioral changes are analogous to drug-induced delirium and sundowning seen in older adults. Future mechanistic investigations are needed to further inform considerations of age, sex, and polypharmacy to optimize quality use of medicines.

Precision medicine is an approach to maximise the effectiveness of disease treatment and prevention and minimise harm from medications by considering relevant demographic, clinical, genomic and environmental factors in making treatment decisions. Precision medicine is complex, even for decisions about single drugs for single diseases, as it requires expert consideration of multiple measurable factors that affect pharmacokinetics and pharmacodynamics, and many patient-specific variables. Given the increasing number of patients with multiple conditions and medications, there is a need to apply lessons learned from precision medicine in monotherapy and single disease management to optimise polypharmacy. However, precision medicine for optimisation of polypharmacy is particularly challenging because of the vast number of interacting factors that influence drug use and response. In this narrative review, we aim to provide and apply the latest research findings to achieve precision medicine in the context of polypharmacy. Specifically, this review aims to (1) summarise challenges in achieving precision medicine specific to polypharmacy; (2) synthesise the current approaches to precision medicine in polypharmacy; (3) provide a summary of the literature in the field of prediction of unknown drug–drug interactions (DDI) and (4) propose a novel approach to provide precision medicine for patients with polypharmacy. For our proposed model to be implemented in routine clinical practice, a comprehensive intervention bundle needs to be integrated into the electronic medical record using bioinformatic approaches on a wide range of data to predict the effects of polypharmacy regimens on an individual. In addition, clinicians need to be trained to interpret the results of data from sources including pharmacogenomic testing, DDI prediction and physiological-pharmacokinetic-pharmacodynamic modelling to inform their medication reviews. Future studies are needed to evaluate the efficacy of this model and to test generalisability so that it can be implemented at scale, aiming to improve outcomes in people with polypharmacy.

West Nile virus (WNV) is a single-stranded RNA arbovirus of Flavivirus genus that is endemic to the United States and known to cause neuroinvasive disease. Diagnosis is confirmed by the presence of WNV-specific IgM antibodies within serum or cerebrospinal fluid (CSF). Radiologically, it presents as hyperintense T2 signal within deep brain structures (ie, thalami and mid-brain) with or without cerebral peduncle and substantia nigra involvement. On diffusion-weighted imaging, restricted diffusion is reported in basal ganglia and disseminated throughout the white matter. In this report, we describe the imaging findings for 2 cases of WNV from our institution; a 56-year-old female and a 34-year-old female. Increased vigilance for WNV is warranted, particularly in immunosuppressed patients presenting with a clinical picture of viral meningoencephalitis despite initial negative magnetic resonance imaging or CSF analysis. A high suspicion for WNV disease should prompt repeat imaging or laboratory workup.

Abstract There is an unmet need and urgency to find safe and effective anti-obesity interventions. Our recent study in mice fed on obesogenic diet found that treatment with the alcohol aversive drug disulfiram reduced feeding efficiency and led to a decrease in body weight and an increase in energy expenditure. The intervention with disulfiram improved glucose tolerance and insulin sensitivity, and mitigated metabolic dysfunctions in various organs through poorly defined mechanisms. Here, integrated analysis of transcriptomic and proteomic data from mouse and rat livers unveiled comparable signatures in response to disulfiram, revealing pathways associated with lipid and energy metabolism, redox, and detoxification. In cell culture, disulfiram was found to be a potent activator of autophagy, the malfunctioning of which has negative consequences on metabolic regulation. Thus, repurposing disulfiram may represent a potent strategy to combat obesity.

This study compared serum pyridine levels (NAD+ /NADH) in trained (n = 6) and untrained (n = 7) subjects after continuous progressive exercise at 50%, 70% then 95% of physical work capacity until fatigue (TTF) after consuming a placebo or antioxidant (AO) cocktail (Lactaway©). An increase of 17% in TTF was observed in AO as compared to placebo (p = 0.032). This was accompanied by a significant increase in serum NAD+ levels (p = 0.037) in the AO supplemented group post exercise. The increases in NAD+ and improved endurance reflect lower oxidative stress-induced suppression of aerobic respiration.

We have found an error in our manuscript published in Nutrients [...]

Abstract The study was conducted to assess the spatial and temporal variations of the trophic state condition of Lake Bunyonyi between October 2019 and September 2020. Secchi depth (SD), total phosphorus (TP) and chlorophyll-a (Chl-a) concentration were measured to aid the quantification of trophic state condition of the lake using Carlson trophic state index (CTSI). The trophic state index (TSI) values based on SD, TP and Chl-a values were 60.82 ± 5.35, 68.99 ± 11.04 and 61.74 ± 7.51, respectively. March 2020 recorded the highest mean CSTI value (70.14 ± 4.04), while in September 2020, the lowest mean value (58.03 ± 6.22) was obtained. Based on CTSI values, the lake was eutrophic in both dry and wet seasons albeit with differences in the values. The eutrophic state of the lake is possibly attributed to nutrients inflow into the lake via runoff and drainage from farmlands. The negative value of TSI-Chl-a–TSI-TP deviation pointed out that the lake is not phosphorus limited, while the positive TSI-Chl-a–TSI-SD mean deviation value revealed the effect of Chl-a and TP on the lake’s transparency. The study recommends the necessity to develop guidelines for the trophic status monitoring of Lake Bunyonyi since results suggest the deteriorating lake condition.

Abstract Lake Bunyonyi is one of the major resources of social-economic potential in the districts of Rubanda and Kabale, South-Western Uganda. The lake’s sub-catchment faces environmental problems because of intensive agriculture, settlement, business and tourism activities, which consequently cause pollution of water in the lake’s system. This study, therefore, intended to determine the processes that govern nitrogen dynamism using a numerical model that takes into account various processes in the system using STELLA® 8.1.1 software. From the model simulation, it was found that mineralization, microbial uptake and nitrification were the major processes governing nitrogen transformation in the water phase, accounting for 47.8% (0.49 g/d m−2), 44.2% (0.45 g/d m−2), and 7.8% (0.05 g/d m−2), respectively. The developed model predicted reasonably well the behaviour of the lake evidenced by the validation results of observed and simulated data that showed good linear regression coefficients (R 2) of organic nitrogen (0.48), ammonia–nitrogen (0.68), and nitrate–nitrogen (0.61). The model has proven suitable for application on lakes with characteristics similar to that of Lake Bunyonyi. The study recommended that a compressive investigation that puts into consideration all the possible sources of nutrient and water inflow into the lake system be done on Lake Bunyonyi.

BackgroundSingle nucleotide polymorphisms (SNPs) interfere with the function of certain genes and thus may influence the probability of skin cancer. The correlation between SNPs and skin cancer (SC) lacks statistical power, however. Therefore, the purpose of this study was to identify the gene polymorphisms involved in skin cancer susceptibility using network meta-analysis and to determine the relationship between SNPs and SC risk.MethodsPubMed, Embase, and Web of Science were searched for articles including “SNP” and different types of SC as keywords between January 2005 and May 2022. The Newcastle-Ottawa Scale was used to assess bias judgments. The odds ratio (ORs) and their 95% confidence intervals (CIs) were determined to estimate heterogeneity within and between studies. Meta-analysis and network meta-analysis were carried out to identify the SNPs associated with SC. The P-score of each SNP was compared to obtain the rank of probability. Subgroup analyses were performed by cancer type.ResultsA total of 275 SNPs from 59 studies were included in the study. Two subgroup SNP networks using the allele model and dominant model were analyzed. The alternative alleles of rs2228570 (FokI) and rs13181 (ERCC2) were the first-ranking SNPs in both subgroups one and two of the allele model, respectively. The homozygous dominant genotype and heterozygous genotype of rs475007 in subgroup one and the homozygous recessive genotype of rs238406 in subgroup two were most likely to be associated with skin cancer based on the dominant model.ConclusionsAccording to the allele model, SNPs FokI rs2228570 and ERCC2 rs13181 and, according to the dominant model, SNPs MMP1 rs475007 and ERCC2 rs238406 are closely linked to SC risk.

Abstract The current study was carried out to examine the spatial and temporal variations of physicochemical water quality parameters of Lake Bunyonyi. The observations were made on the surface water of Lake Bunyonyi for 1 year to determine the water quality. The basic 12 variables used to determine the quality of water were measured monthly at nine stations. Water temperature, dissolved oxygen (DO), turbidity, electric conductivity (EC), pH and Secchi depth (SD) were measured in the field, while parameters like total nitrogen (TN), total phosphorus (TP), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N), soluble reactive phosphorus (SRP) were determined following APHA 2017 standard guidelines for physicochemical analysis. Taking into account standard guidelines for drinking water by the Uganda National Bureau of Standards (UNBS) and the World Health Organization (WHO), the water quality index (WQI) was used to determine the water quality. Temperature, DO, pH, turbidity and EC did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p 0.05) but showed significant temporal variations among the study months (p

Abstract Background Microbial water quality serves to indicate health risks associated with the consumption of contaminated water. Nevertheless, little is known about the microbiological characteristics of water in Lake Bunyonyi. This study was therefore undertaken to examine the spatial and temporal variations of faecal indicator bacteria (FIB) in relation to physicochemical parameters in Lake Bunyonyi. Result The FIB concentration was consistently measured during sampling months and correlated with each other showing the presumed human faecal pollution in the lake. The highest concentration values for E. coli (64.7 ± 47.3 CFU/100 mL) and enterococci (24.6 ± 32.4 CFU/100 mL were obtained in the station close to the Mugyera trading centre. On a temporal basis, the maximum values were recorded during the rainy season in October 2019 (70.7 ± 56.5 CFU/100 mL for E. coli and 38.44 ± 31.8 CFU/100 mL for enterococci. FIB did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the months (p

Kala-azar is a parasitic disease caused by Leishmania species transmitted by sand fly. In Kenya, kala-azar is endemic in thirty subcounties spread over in eleven counties in the arid zones. Climate change-influenced seasonal weather variability and environmental alterations remain important determinants of many vector-borne diseases. The present study focused on climate change and environmental influence on kala-azar in West Pokot. A descriptive cross-sectional and retrospective research design was adapted. Study area was purposively selected. Locations were randomly selected, and households were systematically selected. Three hundred sixty-three household questionnaires, eleven key informant interviews, and five focus group discussions were undertaken. Secondary data were obtained from Kacheliba subcounty hospital records. Statistical Package for the Social Sciences version 24 was used to analyze quantitative data while qualitative data were analyzed to establish connection for interpretation. Kala-azar cases have been on the rise on aggregate and surge towards the end of dry season and just after the rains. Significant environmental factors included the presence of seasonal rain water pathways and rock piles around houses (AOR = 4.7; 95% CI = (2.3-9.6), p

We define a new type of vertex coloring which generalizes vertex coloring in graphs, hypergraphs, andsimplicial complexes. To this coloring there is an associated symmetric function in noncommuting variables for whichwe give a deletion-contraction formula. In the case of graphs our symmetric function in noncommuting variablesagrees with the chromatic symmetric function in noncommuting variables of Gebhard and Sagan. Our vertex coloringis a special case of the scheduling problems defined by Breuer and Klivans. We show how the deletion-contractionlaw can be applied to scheduling problems.

Edible insects are increasingly being considered as sustainable alternatives to fish and soybean meals in animal feed because of their high nutritional quality and environmental benefits. However, successful introduction of a new product to the market depends on the target user's acceptance. Thus, evaluating the potential demand of insect-based feeds would provide relevant information for policy development. The present study assessed farmers' knowledge on edible insects as feed, their acceptance of integrating insect meals in animal feeds and willingness to pay (WTP) for insect-based feed (IBF) using a contingent valuation method. A household survey was conducted among 957 randomly selected farmers including: 409 poultry, 241 fish and 307 pig farmers in four counties in Kenya. Results of the study reveal that over 70 and 80% of poultry and fish farmers, respectively, are aware that insects can be used as a feed ingredient. In addition, over 60 and 75% of poultry and fish farmers, respectively, consider insects as a good component of feed. Poultry, pig and fish farmers interviewed accepted and showed willingness to pay for IBF. Regression analysis indicated that age, gender, education, marital status, distance to feed trader, awareness of insects as feed, attitude towards insects, acceptance of insect species, availability of agricultural inputs, use of commercial feeds, availability of training and market information had a significant influence on the WTP for IBF. Therefore, increased extension services to educate famers on the nutritional benefits of insect meals in animal feeds and existing market opportunities are expected to improve farmers' attitude towards utilization and consequently enhance WTP for IBF, which in return would significantly reduce the existing pressure on conventional fishmeal feed resources. Our findings provide the first insights into the market opportunities of including insect meals in the animal feed value chain in Kenya.

The Andean cat is a rarest wildcat of South America, categorized as Endangered by IUCN. Its habitat is in the high Andes of Argentina, Bolivia, Chile and Peru. In Peru, it has been reported in nine departments, and in four natural protected areas. We present two records from Salinas y Aguada Blanca National Reserve from early 2015, in two different locations. The first was near the Pillones village and the second near to Viscachani village; those are the first image record for Salinas y Aguada Blanca National Reserve; previous records were from skins and fecal DNA. Both records are the most recent from Peru and the very firsts complete images of full Andean cats live in the county.

We consider a Hopf algebra of simplicial complexes and provide a cancellation-free formula for its antipode. We then obtain a family of combinatorial Hopf algebras by defining a family of characters on this Hopf algebra. The characters of these Hopf algebras give rise to symmetric functions that encode information about colorings of simplicial complexes and their $f$-vectors. We also use characters to give a generalization of Stanley’s $(-1)$-color theorem.

Understanding and managing water quality in drinking water distribution system is essential for public health and wellbeing, but is challenging due to the number and complexity of interacting physical, chemical and biological processes occurring within vast, deteriorating pipe networks. In this paper we explore the application of Self Organising Map techniques to derive such understanding from international data sets, demonstrating how multivariate, non-linear techniques can be used to identify relationships that are not discernible using univariate and/or linear analysis methods for drinking water quality. The paper reports on how various microbial parameters correlated with modelled water ages and were influenced by water temperatures in three drinking water distribution systems.

We investigate solving semidefinite programs (SDPs) with an interior point method called SDP-CUT, which utilizes weighted analytic centers and cutting plane constraints. SDP-CUT iteratively refines the feasible region to achieve the optimal solution. The algorithm uses Newton’s method to compute the weighted analytic center. We investigate different stepsize determining techniques. We found that using Newton's method with exact line search is generally the best implementation of the algorithm. We have also compared our algorithm to the SDPT3 method and found that SDP-CUT initially gets into the neighborhood of the optimal solution in less iterations on all our test problems. SDP-CUT also took less iterations to reach optimality on many of the problems. However, SDPT3 required less iterations on most of the test problems and less time on all the problems. Some theoretical properties of the convergence of SDP-CUT are also discussed.