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The Arduino inventor's guide: learn electronics by making 10 awesome projects
\"A hands-on introduction to exploring electronics with Arduino for beginners\"-- Provided by publisher.
Book
Lung Cancer: Diagnosis, Treatment Principles, and Screening
Lung cancer is the second most common cancer in men and women in the United States; however, it remains the leading cause of cancer-related death in the United States and worldwide. The most common but nonspecific symptom of lung cancer is cough. Associated symptoms, including hemoptysis or shortness of breath, or systemic symptoms, including anorexia or weight loss, greatly increase the likelihood of having lung cancer. Referral to a multidisciplinary lung cancer team, imaging, and confirmation through sputum cytology, thoracentesis, fine-needle aspiration, or mediastinoscopy are recommended. If lung cancer is confirmed, treatment options vary based on staging, histology, immunotherapy biomarker testing, and patient health status. Treatments include surgical resection, immunotherapy, chemotherapy, and/or radiotherapy. Family physicians should focus on primary prevention of lung cancer by encouraging tobacco cessation and early recognition by screening at-risk individuals and following guidelines for pulmonary nodules. As of 2021, the U.S. Preventive Services Task Force recommends annual lung cancer screening using low-dose computed tomography starting at 50 years of age in patients with a 20 pack-year history.
Journal Article
Transcriptional programming in a Bacteroides consortium
Bacteroides
species are prominent members of the human gut microbiota. The prevalence and stability of
Bacteroides
in humans make them ideal candidates to engineer as programmable living therapeutics. Here we report a biotic decision-making technology in a community of
Bacteroides
(consortium transcriptional programming) with genetic circuit compression. Circuit compression requires systematic pairing of engineered transcription factors with cognate regulatable promoters. In turn, we demonstrate the compression workflow by designing, building, and testing all fundamental two-input logic gates dependent on the inputs isopropyl-β-D-1-thiogalactopyranoside and D-ribose. We then deploy complete sets of logical operations in five human donor
Bacteroides
, with which we demonstrate sequential gain-of-function control in co-culture. Finally, we couple transcriptional programs with CRISPR interference to achieve loss-of-function regulation of endogenous genes—demonstrating complex control over community composition in co-culture. This work provides a powerful toolkit to program gene expression in
Bacteroides
for the development of bespoke therapeutic bacteria.
Bacteroides
species are prominent members of the human gut microbiota. Here the authors develop a platform technology (consortium transcriptional programming) in five human donor Bacteroides chassis cells—enabling complex decision-making within said community, which can be used for the development of living therapeutics.
Journal Article
Engineering intelligent chassis cells via recombinase-based MEMORY circuits
Synthetic biologists seek to engineer intelligent living systems capable of decision-making, communication, and memory. Separate technologies exist for each tenet of intelligence; however, the unification of all three properties in a living system has not been achieved. Here, we engineer completely intelligent
Escherichia coli
strains that harbor six orthogonal and inducible genome-integrated recombinases, forming Molecularly Encoded Memory via an Orthogonal Recombinase arraY (MEMORY). MEMORY chassis cells facilitate intelligence via the discrete multi-input regulation of recombinase functions enabling inheritable DNA inversions, deletions, and genomic insertions. MEMORY cells can achieve programmable and permanent gain (or loss) of functions extrachromosomally or from a specific genomic locus, without the loss or modification of the MEMORY platform – enabling the sequential programming and reprogramming of DNA circuits within the cell. We demonstrate all three tenets of intelligence via a probiotic (Nissle 1917) MEMORY strain capable of information exchange with the gastrointestinal commensal
Bacteroides thetaiotaomicron
.
The unification of decision-making, communication, and memory would enable the programming of intelligent biotic systems. Here, the authors achieve this goal by engineering
E. coli
chassis cells with an array of inducible recombinases that mediate diverse genetic programs.
Journal Article
The Causal Effect of Intrapancreatic Fat Deposition on Acute and Chronic Pancreatitis: A Mendelian Randomization Study
INTRODUCTION:Recent associative studies have linked intrapancreatic fat deposition (IPFD) with risk of pancreatitis, but the causal relationship remains unclear.METHODS:Using Mendelian randomization, we evaluated the causal association between genetically predicted IPFD and pancreatitis. This approach used genetic variants from genomewide association studies of IPFD (n = 25,617), acute pancreatitis (n = 6,787 cases/361,641 controls), and chronic pancreatitis (n = 3,875 cases/361,641 controls).RESULTS:Genetically predicted IPFD was significantly associated with acute pancreatitis (odds ratio per 1-SD increase: 1.40 [95% CI: 1.12-1.76], P = 0.0032) and chronic pancreatitis (odds ratio: 1.64 [95% CI: 1.13-2.39], P = 0.0097).DISCUSSION:Our findings support a causal role of IPFD in pancreatitis, suggesting that reducing IPFD could lower the risk of pancreatitis.
Journal Article
Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System
BackgroundThe demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified.ObjectiveTo describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use.DesignObservational cohort study.PatientsA total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California.Main MeasuresOverall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19.Key ResultsHealthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15–1.41), female gender (RR 1.07, 95% CI 1.05–1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03–1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization.ConclusionsPatients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.
Journal Article
Engineering wetware and software for the predictive design of compressed genetic circuits for higher-state decision-making
Synthetic genetic circuits enable the reprogramming of cells, advancing the study and application of biology with greater precision. However, quantitative circuit design is hampered by the limited modularity of biological parts. As circuit complexity increases, this imposes a greater metabolic burden on chassis cells, which limits circuit design capacity. Here, we present a generalizable wetware and complementary software to enable the quantitative design of genetic circuits that utilize fewer parts for higher-state decision-making. We term the process of designing smaller genetic circuits as compression. To accomplish this, we develop scalable wetware that leverages sets of synthetic transcription factors (i.e., network capable repressors and anti-repressors) and synthetic promoters that facilitate the full development of 3-input Boolean logic compression circuits. Complementary software enables the design of higher-state circuits with a minimal genetic footprint and quantitatively precise performance setpoints. On average the resulting multi-state compression circuits are approximately 4-times smaller than canonical inverter-type genetic circuits. Our quantitative predictions have an average error below 1.4-fold for >50 test cases. Additionally, we successfully apply this technology toward the predictive design of a recombinase genetic memory circuit, and flux through a metabolic pathway with precise setpoints.
As the complexity of synthetic genetic circuits increases for biocomputing applications, there is a need to reduce the footprint of circuits to reduce burden on cells. Here, the authors develop wetware and software to design 3-input Boolean logic circuits that utilize fewer genetic parts.
Journal Article
The benefits and harms of adjuvant chemotherapy for non-small cell lung cancer in patients with major comorbidities: A simulation study
Randomized controlled trials (RCTs) have demonstrated a survival benefit for adjuvant platinum-based chemotherapy after resection of locoregional non-small cell lung cancer (NSCLC). The relative benefits and harms and optimal approach to treatment for NSCLC patients who have major comorbidities (chronic obstructive pulmonary disease [COPD], coronary artery disease [CAD], and congestive heart failure [CHF]) are unclear, however.
We used a simulation model to run in-silico comparative trials of adjuvant chemotherapy versus observation in locoregional NSCLC in patients with comorbidities. The model estimated quality-adjusted life years (QALYs) gained by each treatment strategy stratified by age, comorbidity, and stage. The model was parameterized using outcomes and quality-of-life data from RCTs and primary analyses from large cancer databases.
Adjuvant chemotherapy was associated with clinically significant QALY gains for all patient age/stage combinations with COPD except for patients >80 years old with Stage IB and IIA cancers. For patients with CHF and Stage IB and IIA disease, adjuvant chemotherapy was not advantageous; in contrast, it was associated with QALY gains for more advanced stages for younger patients with CHF. For stages IIB and IIIA NSCLC, most patient groups benefited from adjuvant chemotherapy. However, In general, patients with multiple comorbidities benefited less from adjuvant chemotherapy than those with single comorbidities and women with comorbidities in older age categories benefited more from adjuvant chemotherapy than their male counterparts.
Older, multimorbid patients may derive QALY gains from adjuvant chemotherapy after NSCLC surgery. These results help extend existing clinical trial data to specific unstudied, high-risk populations and may reduce the uncertainty regarding adjuvant chemotherapy use in these patients.
Journal Article
Synthesizing cellular LOGIC
Engineering synthetic tools that facilitate decision-making in mammalian cells could enable myriad biomedical applications. Researchers have now developed a new system of inducer-controlled transcription factors to facilitate synthetic decision-making (LOGIC) in human cells based on modular protein-fusion cascades.
Journal Article
Racial/ethnic differences in risk factors for non-cardia gastric cancer: an analysis of the Multiethnic Cohort (MEC) Study
Purpose
Gastric cancer (GC) incidence rates show notable differences by racial/ethnic groups in the US. We sought to determine whether stratification by race/ethnicity would reveal unique risk factors for development of non-cardia gastric cancer (NCGC) for US population.
Methods
Analysis included 1,112 incident cases of NCGC and 190,883 controls from the Multiethnic Cohort Study, a prospective US cohort study that recruited individuals living in Hawaii and California, aged 45–75 years from 5 races/ethnicities. Descriptive analysis and Cox regression models examined the association of risk factors for GC and calculate hazard ratios for each race/ethnicity, adjusting for sociodemographic and dietary variables.
Results
Increasing age and male sex were risk factors for NCGC for most race/ethnicities. Higher risk was associated with: GC family history for Latino and Japanese American individuals [HRs range from 1.75 to 1.98]; foreign-born for Japanese American individuals [HR: 1.52, 95% CI 1.11–2.09]; lower education for African American, Japanese American, and Native Hawaiian individuals [HRs range from 1.30 to 1.74]; daily alcohol consumption for African American individuals[HR: 1.56, 95% CI 1.04–2.35]; current smoking for Latino and Japanese American individuals [HRs range from 1.89 to 1.94]; sodium consumption in the highest quartile for White individuals [HR: 2.55, 95% CI 1.23–5.26] compared to the lowest quartile; fruit consumption in the 2nd, 3rd, and 4th highest quartile for Native Hawaiian individuals [HRs range from 2.19 to 2.60] compared to the lowest quartile; diabetes for African American individuals [HR: 1.79, 95% CI 1.21–2.64]; and gastric/duodenal ulcers for Native Hawaiian individuals [HR: 1.82, 95% CI 1.04–3.18].
Conclusion
Analyses by racial/ethnic group revealed differing risk factors for NCGC. Increased knowledge of the varying pathways to GC can support personalized GC prevention strategies and risk stratification tools for early detection.
Journal Article