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This paper examines how firm investments in technology-based employee monitoring impact both misconduct and productivity. We use unique and detailed theft and sales data from 392 restaurant locations from five firms that adopt a theft monitoring information technology (IT) product. We use difference-in-differences models with staggered adoption dates to estimate the treatment effect of IT monitoring on theft and productivity. We find significant treatment effects in reduced theft and improved productivity that appear to be primarily driven by changed worker behavior rather than worker turnover. We examine four mechanisms that may drive this productivity result: economic and cognitive multitasking, fairness-based motivation, and perceived increases of general oversight. The observed productivity results represent substantial financial benefits to both firms and the legitimate tip-based earnings of workers. Our results suggest that employee misconduct is not solely a function of individual differences in ethics or morality, but can also be influenced by managerial policies that can benefit both firms and employees. This paper was accepted by Serguei Netessine, operations management .

During technological discontinuities, incumbents frequently develop hybrids of competing technical generations. Although some prior work implies that such intergenerational hybrids may be the result of organizational dysfunction, we propose that in some cases hybrids may be sophisticated learning tools that shape organizational adaptation to a technological discontinuity. In this paper, we suggest two mechanisms through which intergenerational hybrids may affect organizational adaptation: spillbacks and spillforwards. In an empirical test among the population of automobile carburetor manufacturers during a technological discontinuity, we observe that organizations developing intergenerational hybrids capture spillback benefits—knowledge spillovers from an emerging technology generation to the current generation. Furthermore, we find that these same organizations also capture spillforwards—spillover benefits from developing higher-performing intergenerational hybrids that improve their product performance in the future technology generation. These results suggest that intergenerational hybrids may be stepping-stones for organizations to learn about and adapt to technology discontinuities.

Cancer cells have higher reactive oxygen species (ROS) than normal cells, due to genetic and metabolic alterations. An emerging scenario is that cancer cells increase ROS to activate protumorigenic signaling while activating antioxidant pathways to maintain redox homeostasis. Here we show that, in basal-like and BRCA1-related breast cancer (BC), ROS levels correlate with the expression and activity of the transcription factor aryl hydrocarbon receptor (AhR). Mechanistically, ROS triggers AhR nuclear accumulation and activation to promote the transcription of both antioxidant enzymes and the epidermal growth factor receptor (EGFR) ligand, amphiregulin (AREG). In a mouse model of BRCA1-related BC, cancer-associated AhR and AREG control tumor growth and production of chemokines to attract monocytes and activate proangiogenic function of macrophages in the tumor microenvironment. Interestingly, the expression of these chemokines as well as infiltration of monocyte-lineage cells (monocyte and macrophages) positively correlated with ROS levels in basal-like BC. These data support the existence of a coordinated link between cancer-intrinsic ROS regulation and the features of tumor microenvironment. Therapeutically, chemical inhibition of AhR activity sensitizes human BC models to Erlotinib, a selective EGFR tyrosine kinase inhibitor, suggesting a promising combinatorial anticancer effect of AhR and EGFR pathway inhibition. Thus, AhR represents an attractive target to inhibit redox homeostasis and modulate the tumor promoting microenvironment of basal-like and BRCA1-associated BC.

Interactions between nuclear and mitochondrial gene products are critical for eukaryotic cell function. Nuclear genes encoding mitochondrial-targeted proteins (N-mt genes) experience elevated rates of evolution, which has often been interpreted as evidence of nuclear compensation in response to elevated mitochondrial mutation rates. However, N-mt genes may be under relaxed functional constraints, which could also explain observed increases in their evolutionary rate. To disentangle these hypotheses, we examined patterns of sequence and structural evolution in nuclear- and mitochondrial-encoded oxidative phosphorylation proteins from species in the angiosperm genus Silene with vastly different mitochondrial mutation rates. We found correlated increases in N-mt gene evolution in species with fast-evolving mitochondrial DNA. Structural modeling revealed an overrepresentation of N-mt substitutions at positions that directly contact mutated residues in mitochondrial-encoded proteins, despite overall patterns of conservative structural evolution. These findings support the hypothesis that selection for compensatory changes in response to mitochondrial mutations contributes to the elevated rate of evolution in N-mt genes. We discuss these results in light of theories implicating mitochondrial mutation rates and mitonuclear coevolution as drivers of speciation and suggest comparative and experimental approaches that could take advantage of heterogeneity in rates of mtDNA evolution across eukaryotes to evaluate such theories.

In the absence of an effective treatment for non-alcoholic steatohepatitis (NASH), a randomized, placebo-controlled trial (RCT) remains the current gold standard study design in NASH. As NASH is a largely asymptomatic disease, the side effects of potential therapies require careful evaluation, therefore a pooled rate of the adverse events (AEs) in placebo-treated patients serves as a useful comparator for safety. Therefore, we performed a systematic review and meta-analysis to estimate the rate of AEs among participants in the placebo arm of NASH RCTs. Medline, Embase and Cochrane Central Register of Controlled Trials were searched to include clinical trials in phase 2-4 NASH RCTs with placebo treatment arms. A pooled proportions of AEs were analyzed using a generalized linear mixed model with Clopper-Pearson intervals. A total of 41 RCTs (2,944 participants on placebo) were included in this meta-analysis. A total of 68% (confidence interval [CI] 55%-77%) of participants on placebo experienced an AE, 7.8% (5.7%-10%) experienced serious AEs and 3.1% (CI: 1.9%-5.1%) experienced AEs leading to discontinuation. A significantly higher proportion of participants experienced serious AEs in phase 3 studies compared to in phase 2 studies ( P < 0.01) and in pharmaceutical funded studies as compared to studies which were federal-funded studies ( P < 0.01). An analysis of clinical trials evaluating bile acid modulating agents determined that 10% (CI: 5.5%-18%) of participants receiving placebo developed pruritus. The present study summarizes the AEs with NASH placebo. Among participants in the placebo arm in NASH, two-third experienced an AE, and nearly 10% experienced a serious AE.

The characteristics of joint acoustic emissions (JAEs) measured from the knee have been shown to contain information regarding underlying joint health. Researchers have developed methods to process JAE measurements and combined them with machine learning algorithms for knee injury diagnosis. While these methods are based on JAEs measured in controlled settings, we anticipate that JAE measurements could enable accessible and affordable diagnosis of acute knee injuries also in field-deployable settings. However, in such settings, the noise and interference would be greater than in sterile, laboratory environments, which could decrease the performance of existing knee health classification methods using JAEs. To address the need for an objective noise and interference detection method for JAE measurements as a step towards field-deployable settings, we propose a novel experimental data augmentation method to locate and then, remove the corrupted parts of JAEs measured in clinical settings. In the clinic, we recruited 30 participants, and collected data from both knees, totaling 60 knees (36 healthy and 24 injured knees) to be used subsequently for knee health classification. We also recruited 10 healthy participants to collect artifact and joint sounds (JS) click templates, which are audible, short duration and high amplitude JAEs from the knee. Spectral and temporal features were extracted, and clinical data was augmented in five-dimensional subspace by fusing the existing clinical dataset into experimentally collected templates. Then knee scores were calculated by training and testing a linear soft classifier utilizing leave-one-subject-out cross-validation (LOSO-CV). The area under the curve (AUC) was 0.76 for baseline performance without any window removal with a logistic regression classifier (sensitivity = 0.75, specificity = 0.78). We obtained an AUC of 0.86 with the proposed algorithm (sensitivity = 0.80, specificity = 0.89), and on average, 95% of all clinical data was used to achieve this performance. The proposed algorithm improved knee health classification performance by the added information through identification and collection of common artifact sources in JAE measurements. This method when combined with wearable systems could provide clinically relevant supplementary information for both underserved populations and individuals requiring point-of-injury diagnosis in field-deployable settings.

Background and objectivesThe clinical diagnosis of Huntington disease (HD) is typically made once motor symptoms and chorea are evident. Recent reports highlight the onset of cognitive and psychiatric symptoms before motor manifestations. These findings support further investigations of cognitive function across the lifespan of HD sufferers.MethodsTo assess cognitive symptoms in the developing brain, we administered assessments from the National Institutes of Health Toolbox Cognitive Battery, an age-appropriate cognitive assessment with population norms, to a cohort of children, adolescents and young adults with (gene-expanded; GE) and without (gene-not-expanded; GNE) the trinucleotide cytosine, adenine, guanine (CAG) expansion in the Huntingtin gene. These five assessments that focus on executive function are well validated and form a composite score, with population norms. We modelled these scores across age, and CAP score to estimate the slope of progression, comparing these results to motor symptoms.ResultsWe find significant deficits in the composite measure of executive function in GE compared with GNE participants. GE participant performance on working memory was significantly lower compared with GNE participants. Modelling these results over age suggests that these deficits occur as early as 18 years of age, long before motor manifestations of HD.ConclusionsThis work provides strong evidence that impairments in executive function occur as early as the second decade of life, well before anticipated motor onset. Future investigations should delineate whether these impairments in executive function are due to abnormalities in neurodevelopment or early sequelae of a neurodegenerative process.

The most common malignant brain tumour in children, medulloblastoma (MB), is subdivided into four clinically relevant molecular subgroups, although targeted therapy options informed by understanding of different cellular features are lacking. Here, by comparing the most aggressive subgroup (Group 3) with the intermediate (SHH) subgroup, we identify crucial differences in tumour heterogeneity, including unique metabolism-driven subpopulations in Group 3 and matrix-producing subpopulations in SHH. To analyse tumour heterogeneity, we profiled individual tumour nodules at the cellular level in 3D MB hydrogel models, which recapitulate subgroup specific phenotypes, by single cell RNA sequencing (scRNAseq) and 3D OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) imaging. In addition to identifying known metabolites characteristic of MB, we observed intra- and internodular heterogeneity and identified subgroup-specific tumour subpopulations. We showed that extracellular matrix factors and adhesion pathways defined unique SHH subpopulations, and made up a distinct shell-like structure of sulphur-containing species, comprising a combination of small leucine-rich proteoglycans (SLRPs) including the collagen organiser lumican. In contrast, the Group 3 tumour model was characterized by multiple subpopulations with greatly enhanced oxidative phosphorylation and tricarboxylic acid (TCA) cycle activity. Extensive TCA cycle metabolite measurements revealed very high levels of succinate and fumarate with malate levels almost undetectable particularly in Group 3 tumour models. In patients, high fumarate levels (NMR spectroscopy) alongside activated stress response pathways and high Nuclear Factor Erythroid 2-Related Factor 2 (NRF2; gene expression analyses) were associated with poorer survival. Based on these findings we predicted and confirmed that NRF2 inhibition increased sensitivity to vincristine in a long-term 3D drug treatment assay of Group 3 MB. Thus, by combining scRNAseq and 3D OrbiSIMS in a relevant model system we were able to define MB subgroup heterogeneity at the single cell level and elucidate new druggable biomarkers for aggressive Group 3 and low-risk SHH MB.

Non-alcoholic steatohepatitis (NASH) is a common form of chronic liver disease characterised by lipid accumulation, infiltration of immune cells, hepatocellular ballooning, collagen deposition and liver fibrosis. There is a high unmet need to develop treatments for NASH. We have investigated how liver fibrosis and features of advanced clinical disease can be modelled using an in vitro microphysiological system (MPS). The NASH MPS model comprises a co-culture of primary human liver cells, which were cultured in a variety of conditions including+/− excess sugar, fat, exogenous TGFβ or LPS. The transcriptomic, inflammatory and fibrotic phenotype of the model was characterised and compared using a system biology approach to identify conditions that mimic more advanced clinical disease. The transcriptomic profile of the model was shown to closely correlate with the profile of patient samples and the model displayed a quantifiable fibrotic phenotype. The effects of Obeticholic acid and Elafibranor, were evaluated in the model, as wells as the effects of dietary intervention, with all able to significantly reduce inflammatory and fibrosis markers. Overall, we demonstrate how the MPS NASH model can be used to model different aspects of clinical NASH but importantly demonstrate its ability to model advanced disease with a quantifiable fibrosis phenotype.Kostrzewski et al. introduce an in vitro microphysiological model of non-alcoholic steatohepatitis (NASH), consisting of co-cultured primary human liver cells. The authors characterised the transcriptomic, inflammatory and fibrotic phenotype of the model and show that major features of NASH can be recapitulated and therapeutic interventions mimicked.

COVID-19 has caused nearly 1 million deaths in the United States, not to mention job losses, business and school closures, stay-at-home orders, and mask mandates. Many people have suffered increased anxiety and depression since the pandemic began. Not only have mental health symptoms become more prevalent, but alcohol consumption has also increased during this time. Helplines offer important insight into both physical and mental wellness of a population by offering immediate, anonymous, cheap, and accessible resources for health and substance use disorders (SUD) that was unobstructed by many of the mandates of the pandemic. Further, the pandemic also launched the use of wastewater surveillance, which has the potential for tracking not only population infections but also consumption of substances such as alcohol. This study assessed the feasibility of using multiple public surveillance metrics, such as helpline calls, COVID-19 cases, and alcohol metabolites in wastewater, to better understand the need for interventions or public health programs in the time of a public health emergency. Ethanol metabolites were analyzed from wastewater collected twice weekly from September 29 to December 4, 2020, in a Midwestern state. Calls made to the helpline regarding housing, health care, and mental health/SUD were correlated with ethanol metabolites analyzed from wastewater samples, as well as the number of COVID-19 cases during the sampling period. Correlations were observed between COVID-19 cases and helpline calls regarding housing and health care needs. No correlation was observed between the number of COVID-19 cases and mental health/SUD calls. COVID-19 cases on Tuesdays were correlated with the alcohol metabolite ethyl glucuronide (EtG). Finally, EtG levels were negatively associated with mental health/SUD helpline calls. Although helpline calls provided critical services for health care and housing-related concerns early in the pandemic, evidence suggests helpline calls for mental health/SUD-related concerns were unrelated to COVID-19 metrics. Instead, COVID metrics were associated with alcohol metabolites in wastewater. Although this research was formative, with continued and expanded monitoring of population metrics, such as helpline usage, COVID-19 metrics, and wastewater, strategies can be implemented to create precision programs to address the needs of the population.