Institutional Forces and Knowledge Search Strategies as Predictors of Entrepreneurial Venture Performance

Acknowledgment We are grateful to JSBM editor Eric Liguori and three anonymous reviewers for insightful comments on previous versions of this paper. We also acknowledge the guidance and input from Haiyang Li, the International Finance Corporation’s Enterprise Surveys program, and the Chinese National Bureau of Statistics. This research was supported by grants SRG2019-00146-FBA and CPG2020-00018-FBA awarded to Jean Jinghan Chen by the University of Macau.Peer reviewedPostprin

Enhancing Timeliness of Drug Overdose Mortality Surveillance: A Machine Learning Approach

BACKGROUND: Timely data is key to effective public health responses to epidemics. Drug overdose deaths are identified in surveillance systems through ICD-10 codes present on death certificates. ICD-10 coding takes time, but free-text information is available on death certificates prior to ICD-10 coding. The objective of this study was to develop a machine learning method to classify free-text death certificates as drug overdoses to provide faster drug overdose mortality surveillance. METHODS: Using 2017–2018 Kentucky death certificate data, free-text fields were tokenized and features were created from these tokens using natural language processing (NLP). Word, bigram, and trigram features were created as well as features indicating the part-of-speech of each word. These features were then used to train machine learning classifiers on 2017 data. The resulting models were tested on 2018 Kentucky data and compared to a simple rule-based classification approach. Documented code for this method is available for reuse and extensions: https://github.com/pjward5656/dcnlp. RESULTS: The top scoring machine learning model achieved 0.96 positive predictive value (PPV) and 0.98 sensitivity for an F-score of 0.97 in identification of fatal drug overdoses on test data. This machine learning model achieved significantly higher performance for sensitivity (p \u3c 0.001) than the rule-based approach. Additional feature engineering may improve the model’s prediction. This model can be deployed on death certificates as soon as the free-text is available, eliminating the time needed to code the death certificates. CONCLUSION: Machine learning using natural language processing is a relatively new approach in the context of surveillance of health conditions. This method presents an accessible application of machine learning that improves the timeliness of drug overdose mortality surveillance. As such, it can be employed to inform public health responses to the drug overdose epidemic in near-real time as opposed to several weeks following events

Supergravity Inflation Free from Harmful Relics

We present a realistic supergravity inflation model which is free from the overproduction of potentially dangerous relics in cosmology, namely moduli and gravitinos which can lead to the inconsistencies with the predictions of baryon asymmetry and nucleosynthesis. The radiative correction turns out to play a crucial role in our analysis which raises the mass of supersymmetry breaking field to intermediate scale. We pay a particular attention to the non-thermal production of gravitinos using the non-minimal Kahler potential we obtained from loop correction. This non-thermal gravitino production however is diminished because of the relatively small scale of inflaton mass and small amplitudes of hidden sector fields.Comment: 10 pages, revtex, 1 eps figure, references added, conclusion section expande

A Randomized Phase II Trial of Pioglitazone for Lung Cancer Chemoprevention in High Risk Current and Former Smokers

Lung cancer chemoprevention, especially in high-risk former smokers, has great potential to reduce lung cancer incidence and mortality. Thiazolidinediones prevent lung cancer in preclinical studies, and diabetics receiving thiazolidinediones have lower lung cancer rates which led to our double-blind, randomized, phase II placebo-controlled trial of oral pioglitazone in high risk current or former smokers with sputum cytologic atypia or known endobronchial dysplasia. Bronchoscopy was performed at study entry and after completing of six months of treatment. Biopsies were histologically scored, and primary endpoint analysis tested worst biopsy scores (Max) between groups; Dysplasia index (DI) and average score (Avg) changes were secondary endpoints. Biopsies also received an inflammation score. The trial accrued 92 subjects (47 pioglitazone, 45 placebo), and 76 completed both bronchoscopies (39 pioglitazone, 37 placebo). Baseline dysplasia was significantly worse for current smokers, and 64% of subjects had mild or greater dysplasia at study entry. Subjects receiving pioglitazone did not exhibit improvement in bronchial dysplasia. Former smokers treated with pioglitazone exhibited a slight improvement in Max, while current smokers exhibited slight worsening. While statistically significant changes in Avg and DI were not observed in the treatment group, former smokers exhibited a slight decrease in both Avg and DI. Negligible Avg and DI changes occurred in current smokers. A trend towards decreased Ki-67 labeling index occurred in former smokers with baseline dysplasia receiving pioglitazone. While pioglitazone did not improve endobronchial histology in this high-risk cohort, specific lesions showed histologic improvement and further study is needed to better characterize responsive dysplasia

Potential and Actual Terrestrial Rabies Exposures in People and Domestic Animals, Upstate South Carolina, 1994–2004: A Surveillance Study

<p>Abstract</p> <p>Background</p> <p>Although there has been a reduction of rabies in pets and domestic animals during recent decades in the United States, rabies remains enzootic among bats and several species of terrestrial wildlife. Spillover transmission of wildlife rabies to domestic animals therefore remains a public health threat</p> <p>Methods</p> <p>Retrospective analysis of surveillance data of reported animal incidents (bites, scratches, mucous membrane contacts) from South Carolina, 1995 to 2003, was performed to assess risk factors of potential rabies exposures among human and animal victims.</p> <p>Results</p> <p>Dogs and cats contributed the majority (66.7% and 26.4%, respectively) of all reported incidents, with stray dogs and cats contributing 9.0% and 15.1 respectively. Current rabies vaccination status of dogs and cats (40.2% and 13.8%, respectively) were below World Health Organization recommended levels. Owned cats were half as likely to be vaccinated for rabies as dogs (OR 0.53, 95% CI 0.48, 0.58). Animal victims were primarily exposed to wildlife (83.0%), of which 27.5% were rabid. Almost 90% of confirmed rabies exposures were due to wildlife. Skunks had the highest prevalence of rabies among species of exposure animals (63.2%). Among rabid domestic animals, stray cats were the most commonly reported (47.4%).</p> <p>Conclusion</p> <p>While the majority of reported potential rabies exposures are associated with dog and cat incidents, most rabies exposures derive from rabid wildlife. Stray cats were most frequently rabid among domestic animals. Our results underscore the need for improvement of wildlife rabies control and the reduction of interactions of domestic animals, including cats, with wildlife.</p

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria.

Differentiation of naïve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR sequences, we first demonstrated that Th1/Tfh bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with Th1 or Tfh fates, and demonstrated a T-cell intrinsic role for Galectin-1 in supporting a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards a Th1 but not a Tfh fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources, a database www.PlasmoTH.org, which facilitates discovery of novel factors controlling Th1/Tfh fate commitment, and more generally, GPfates, a modelling framework for characterizing cell differentiation towards multiple fates

Mechanistic and evolutionary insights into isoform-specific ‘supercharging’ in DCLK family kinases

Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The doublecortin-like kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory ‘tail’ segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations, and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to ‘supercharge’ the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other calcium calmodulin kinases (CAMKs), and a ‘Swiss Army’ assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for autoregulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome-wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically divergent DCLK1 modulators, stabilizers, or degraders.</jats:p

Economic Impact of COVID-19 on patients with Type 2 diabetes in Kenya and Tanzania: a costing analysis

Introduction COVID-19 affected healthcare access, utilisation and affordability, especially for patients suffering from chronic diseases, including type 2 diabetes (T2D). This study measured the occurrence and magnitude of changes in healthcare and broader societal costs among patients with T2D before and during COVID-19 in Kenya and Tanzania to understand whether and how COVID-19 affected T2D management in countries implementing different policies during the pandemic. Methods A cross-sectional study was conducted in Kenya and Tanzania in March–April 2022 among 500 patients with T2D in each country. We interviewed patients on direct healthcare costs (eg, inpatient and outpatient costs), societal costs (eg, productivity loss) and patients’ characteristics before and during the COVID-19 pandemic. We estimated changes over time using the Generalised Linear Model in Kenya and a two-part model in Tanzania, adjusting for patient-level covariates. Results The overall costs of management of T2D in most categories increased in both countries during COVID-19, but some of the increase was not significant. Transport and testing costs increased significantly in Tanzania (I0.33, p<0.01 and I0.85, p&lt;0.01) but not in Kenya (I$1.69, p=0.659 and I$0.10, p=0.603). Outpatient costs increased significantly in Tanzania (I8.84, p<0.01) but there was no significant change in Kenya (I8.09, p=0.432). T2D medication costs did not change in Tanzania (I$0.19, p=0.197), but decreased significantly in Kenya (I$18.48, p&lt;0.01). Productivity losses increased significantly in both countries. Conclusion The COVID-19 pandemic is associated with increased direct costs but with a significant increase in many cost categories (transport, testing and outpatient) in Tanzania than in Kenya. A significant increase in productivity loss was observed in both countries. The minimal cost increases in Kenya may be due to the inaccessibility of services associated with lockdown measures and higher insurance coverage compared with Tanzania. Pandemic preparedness initiatives and interventions are needed to safeguard the welfare of patients with chronic conditions during pandemics

Towards a collaborative research: A case study on linking science to farmers' perceptions and knowledge on Arabica coffee pests and diseases and its management

The scientific community has recognized the importance of integrating farmer's perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed. (Résumé d'auteur