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Students and established scholars of intellectual property law often look for historical context when trying to understand the development and present-day contours of IP rules and systems. American Patent Law supplies this context, offering readers a comprehensive account of the evolution of the US patent system and patent doctrine beginning in 1790. From the technologies for harvesting wood and shoemaking in the earliest periods to computer software and biotechnology of the present, each chapter of the book covers the characteristic technologies of each historical era. The book also describes how businesspeople in each era acquired and enforced patents and used patents as the foundation of various business arrangements. This book is a landmark in the history of technologies, the US patent system, and the way private actors have deployed patents across American history.
Aging is a subject of concern to everyone, but is widely misunderstood. If we view it as inevitable, we miss the fact that not everyone is able to grow to an old age. Realization of this reality helps us to understand that aging presents a wonderful opportunity - an opportunity to make choices about how we live which can enhance the aging process and offer a chance to live to our potential. This book clearly presents the four, multiple reserve, factors (cognitive, physical, psychological and social) which impact our ability to have healthy responses to the stresses of aging. By giving the biological basis for the advice given, you will learn the steps to take in your activities, diet and mental outlook to grasp the opportunity that aging offers. Everyone must know that what we do makes a difference.
Previous research has suggested that statistical power is suboptimal in many biomedical disciplines, but it is unclear whether power is better in trials for particular interventions, disorders, or outcome types. We therefore performed a detailed examination of power in trials of psychotherapy, pharmacotherapy, and complementary and alternative medicine (CAM) for mood, anxiety, and psychotic disorders.
Methods
We extracted data from the Cochrane Database of Systematic Reviews (Mental Health). We focused on continuous efficacy outcomes and estimated power to detect predetermined effect sizes (standardized mean difference [SMD] = 0.20–0.80, primary SMD = 0.40) and meta-analytic effect sizes (ESMA). We performed meta-regression to estimate the influence of including underpowered studies in meta-analyses.
Results
We included 256 reviews with 10 686 meta-analyses and 47 384 studies. Statistical power for continuous efficacy outcomes was very low across intervention and disorder types (overall median [IQR] power for SMD = 0.40: 0.32 [0.19–0.54]; for ESMA: 0.23 [0.09–0.58]), only reaching conventionally acceptable levels (80%) for SMD = 0.80. Median power to detect the ESMA was higher in treatment-as-usual (TAU)/waitlist-controlled (0.49–0.63) or placebo-controlled (0.12–0.38) trials than in trials comparing active treatments (0.07–0.13). Adequately-powered studies produced smaller effect sizes than underpowered studies (B = −0.06, p ⩽ 0.001).
Conclusions
Power to detect both predetermined and meta-analytic effect sizes in psychiatric trials was low across all interventions and disorders examined. Consistent with the presence of reporting bias, underpowered studies produced larger effect sizes than adequately-powered studies. These results emphasize the need to increase sample sizes and to reduce reporting bias against studies reporting null results to improve the reliability of the published literature.
This chapter aims to synthesize key findings from the SURE-Farm project. We first discuss possible amendments to the framework to assess the resilience of farming systems. We then review why many of Europe’s farming systems face a formidable and structural resilience crisis. While emphasizing the diversity of resilience capacities, challenges and needs, we formulate cornerstones for possible resilience-enhancing strategies. The chapter concludes with critical reflections and suggestions for resilience-enhancing strategies that comprise the levels of farms, farming systems and enabling environments. We identify limitations of the research and suggest avenues for future research on the resilience of farming systems.
Risk and risk management are essential elements of farming. We show that strategies to cope with risk often go beyond the level of the individual farm. Cooperation, learning and sharing of risks play a vital role in European agriculture. An enabling environment should support cooperative approaches, enable a diversity of risk management solutions and harness novel technological opportunities.
The importance of studying the radiocarbon content of dissolved inorganic carbon (DI14C) in the oceans has been recognized for decades. Starting with the GEOSECS program in the 1970s, 14C sampling has been a part of most global survey programs. Early results were used to study air-sea gas exchange while the more recent results are critical for helping calibrate ocean general circulation models used to study the effects of climate change. Here we summarize the major programs and discuss some of the important insights the results are starting to provide.
A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined.
Aims
To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians’ remote evaluations in predicting mental health disorders.
Method
Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed.
Results
Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value.
Conclusions
Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary–secondary care interface should now be quantified in prospective studies.
OBJECTIVES/GOALS: The goal of this study was to understand the impact of a high sodium diet on gene networks in the kidney that correlate with blood pressure in female primates, and translating findings to women. METHODS/STUDY POPULATION: Sodium-naïve female baboons (n=7) were fed a low-sodium (LS) diet for 6 weeks followed by a high sodium (HS) diet for 6 weeks. Sodium intake, serum 17 beta-estradiol, and ultrasound-guided kidney biopsies for RNA-Seq were collected at the end of each diet. Blood pressure was continuously measured for 64-hour periods throughout the study by implantable telemetry devices. Weighted gene coexpression network analysis was performed on RNA-Seq data to identify transcripts correlated with blood pressure on each diet. Network analysis was performed on transcripts highly correlated with BP, and in silico findings were validated by immunohistochemistry of kidney tissues. RESULTS/ANTICIPATED RESULTS: On the LS diet, Na+ intake and serum 17 beta-estradiol concentration correlated with BP. Cell type composition of renal biopsies was consistent among all animals for both diets. Kidney transcriptomes differed by diet; analysis by unbiased weighted gene co-expression network analysis revealed modules of genes correlated with BP on the HS diet. Network analysis of module genes showed causal networks linking hormone receptors, proliferation and differentiation, methylation, hypoxia, insulin and lipid regulation, and inflammation as regulators underlying variation in BP on the HS diet. Our results show variation in BP correlated with novel kidney gene networks with master regulators PPARG and MYC in female baboons on a HS diet. DISCUSSION/SIGNIFICANCE: Previous studies in primates to identify molecular networks dysregulated by HS diet focused on males. Current clinical guidelines do not offer sex-specific treatment plans for sodium sensitive hypertension. This study leveraged variation in BP as a first step to identify correlated kidney regulatory gene networks in female primates after a HS diet.
In the December 2021 issue of Cardiology in the Young, Hubrechts and colleagues, from Brussels and Leuven in Belgium, describe their experience in which the pulmonary veins were normally connected to the morphologically left atrium. By virtue of the presence of a shelf dividing the morphologically left atrium, however, the venous return was to the morphologically right atrium, with no evidence of formation of the superior interatrial fold, meaning that there was no obstruction of flow into the systemic venous circulation. The question posed by the Belgian authors is whether the shelf dividing the morphologically left atrium is a deviated primary atrial septum, as the arrangement has previously been interpreted. As they discuss, it is currently impossible to arbitrate this conundrum. In our commentary, we discuss the background to the dilemma. We point out that, as yet, it is not possible to code accurately this congenital cardiac malformation within The International Paediatric and Congenital Cardiac Code (IPCCC), nor within the newly produced 11th Revision of the International Classification of Diseases (ICD-11).
OBJECTIVES/GOALS: A functional precision medicine platform to identify therapeutic targets for a glioblastoma patient with Li Fraumeni syndrome was performed. Comparative transcriptomics identified druggable targets and patient derived organoids and a 3D-PREDICT drug screening assay was used to validate the pipeline and identify further therapeutic targets. METHODS/STUDY POPULATION: A comparative transcriptomics pipeline was used to identify druggable genes that are uniquely overexpressed in our patient of interest relative to a cancer compendium of 12,747 tumor RNA sequencing datasets including 200 GBMs. Mini-ring patient derived organoid-based drug viability assays were performed to validate the comparative transcriptomics data. Additionally, a spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. RESULTS/ANTICIPATED RESULTS: Using comparative transcriptomics STAT1 and STAT2 were found to be significantly overexpressed in our patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitor, as a potential therapy. Druggable pathways predicted using comparative transcriptomics corresponded with ruxolitinib sensitivity in a panel of patient derived organoids screened with this compound. Cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. Additionally, 3D-PREDICT screening identified the mTOR inhibitor everolimus as a potential candidate. These two targeted therapies were selected for our patient and resulted in radiographic disease stability. DISCUSSION/SIGNIFICANCE: This research illustrates the use of comparative transcriptomics to identify druggable pathways irrespective of actionable DNA mutations present. Our results are promising and serve to highlight the importance of functional precision medicine in tailoring treatment regimes to specific patients.
OBJECTIVES/GOALS: Low statistical power is a problem is many fields. We performed a systematic review to determine the median statistical power of studies of epilepsy surgery outcomes. METHODS/STUDY POPULATION: We performed a PubMed search for studies reporting epilepsy surgery outcomes for the years 1980-2000, focusing on studies using stereo-electroencephalography (SEEG). We extracted patient count data for comparisons of surgical outcome between groups, based on a prognostic factor. We defined a clinically meaningful difference the surgical outcome for MRI positive (66.9%) compared to MRI negative (45.5%) in the largest study in the series. The statistical power of a Chi-square test was computed as the percentage of simulated runs (10,000 repetitions) assuming this difference with a p-value less than 0.05. RESULTS/ANTICIPATED RESULTS: Based on 69 studies, the median sample size was 38 patients, and the median statistical power was 24%. This implies at least a 17% (0.5/[0.24+0.05)) chance a study with a significant result in false, assuming 1:1 pre-test odds. A 'typical’ SEEG study with 33 patients and 2:1 allocation had a median significant odds ratio of 6.5, which over-estimates the true odds ratio of 2.4. DISCUSSION/SIGNIFICANCE: Studies of epilepsy surgery outcomes using SEEG are statistically underpowered. This means true effects will be missed, the chance a study with a significant result is false will be inflated, and significant effects found will be over-estimated. Studies of surgery outcome need better statistical rigor if they are to reliably guide treatment.
OBJECTIVES/GOALS: Recent research has attempted to identify diagnostic, prognostic, and predictive biomarkers, however, currently, no biomarkers can accurately diagnose GBC and predict patients prognosis. Using machine learning, we can utilize high-throughput RNA sequencing with clinicopathologic data to develop a predictive tool for GBC prognosis. METHODS/STUDY POPULATION: Current predictive models for GBC outcomes often utilize clinical data only. We aim to build a superior algorithm to predict overall survival in GBC patients with advanced disease, using machine learning approaches to prioritize biomarkers for GBC prognosis. We have identified over 80 fresh frozen GBC tissue samples from Rochester, Minnesota, Daegu, Korea, Vilnius, Lithuania, and Calgary, Canada. We will perform next-generation RNA sequencing on these tissue samples. The patients clinical, pathologic and survival data will be abstracted from the medical record. Random forests, support vector machines, and gradient boosting machines will be applied to train the data. Standard 5-fold cross validation will be used to assess performance of each ML algorithm. RESULTS/ANTICIPATED RESULTS: Our preliminary analysis of next generation RNA sequencing from 18 GBC tissue samples identified recurrent mutations in genes enriched in pathways in cytoskeletal signaling, cell organization, cell movement, extracellular matrix interaction, growth, and proliferation. The top three most significantly altered pathways, actin cytoskeleton signaling, hepatic fibrosis/hepatic stellate cell activation, and epithelial adherens junction signaling, emphasized a molecular metastatic and invasive fingerprint in our patient cohort. This molecular fingerprint is consistent with the previous knowledge of the highly metastatic nature of gallbladder tumors and is also manifested physiologically in the patient cohort. DISCUSSION/SIGNIFICANCE: Integrative analysis of molecular and clinical characterization of GBC has not been fully established, and minimal improvement has been made to the survival of these patients. If overall survival can be better predicted, we can gain a greater understanding of key biomarkers driving the tumor phenotype.
We honour a great man and a true giant. Lodewyk H.S. van Mierop (March 31, 1927 – October 17, 2021), known as Bob, was not only a Paediatric Cardiologist but also a dedicated Scientist. He made many significant and ground-breaking contributions to the fields of cardiac anatomy and embryology. He was devoted as a teacher, spending many hours with medical students, Residents, and Fellows, all of whom appreciated his regularly scheduled educational sessions. Those of us who were fortunate to know and spend time with him will always remember his great mind, his willingness to share his knowledge, and his ability to encourage spirited and fruitful discussions. His life was most productive, and he will long be remembered by many through his awesome and exemplary scientific contributions.
His legacy continues to influence the current and future generations of surgeons and all providers of paediatric and congenital cardiac care through the invaluable archive he established at University of Florida in Gainesville: The University of Florida van Mierop Heart Archive. Undoubtedly, with these extraordinary contributions to the fields of cardiac anatomy and embryology, which were way ahead of his time, Professor van Mierop was a true giant in Paediatric Cardiology. The invaluable archive he established at University of Florida in Gainesville, The University of Florida van Mierop Heart Archive, has been instrumental in teaching medical students, Residents, Medical Fellows, and Surgical Fellows. Only a handful of similar archives exist across the globe, and these archives are the true legacy of giants such as Dr. van Mierop. We have an important obligation to leave no stone unturned to continue to preserve these archives for the future generations of surgeons, physicians, all providers of paediatric and congenital cardiac care, and, most importantly, our patients.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
Aims
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
Method
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
Results
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Conclusions
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan.
Methods
This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample.
Results
32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables.
Conclusions
Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments.
Self-control failure occurs when an individual experiences a conflict between immediate desires and longer-term goals, recognises psychological forces that hinder goal-directed action, tries to resist them but fails in the attempt. Behavioural economists often invoke assumptions about self-control failure to justify proposals for policy interventions. These arguments require workable methods for eliciting individuals’ goals and for verifying occurrences of self-control failure, but developing such methods confronts two problems. First, it is not clear that individuals’ goals are context-independent. Second, facing an actual conflict between a desire and a self-acknowledged goal, a person may consciously choose not to resist the desire, thinking that spontaneity is more important than self-control. We address these issues through an online survey that elicited individuals’ self-reported judgements about the relative importance of self-control and spontaneity in conflicts between enjoyment and health-related goals. To test for context-sensitivity, the judgement-elicitation questions were preceded by a memory recall task which directed participants’ attention either to the enjoyment of acting on desires or to the satisfaction of achieving goals. We found little evidence of context-sensitivity. In both treatments, however, judgements that favoured spontaneity were expressed with roughly the same frequency and strength as judgments that favoured self-control.
To quantitatively evaluate relationships between infection preventionists (IPs) staffing levels, nursing hours, and rates of 10 types of healthcare-associated infections (HAIs).
Design and setting:
An ambidirectional observation in a 528-bed teaching hospital.
Patients:
All inpatients from July 1, 2012, to February 1, 2021.
Methods:
Standardized US National Health Safety Network (NHSN) definitions were used for HAIs. Staffing levels were measured in full-time equivalents (FTE) for IPs and total monthly hours worked for nurses. A time-trend analysis using control charts, t tests, Poisson tests, and regression analysis was performed using Minitab and R computing programs on rates and standardized infection ratios (SIRs) of 10 types of HAIs. An additional analysis was performed on 3 stratifications: critically low (2–3 FTE), below recommended IP levels (4–6 FTE), and at recommended IP levels (7–8 FTE).
Results:
The observation covered 1.6 million patient days of surveillance. IP staffing levels fluctuated from ≤2 IP FTE (critically low) to 7–8 IP FTE (recommended levels). Periods of highest catheter-associated urinary tract infection SIRs, hospital-onset Clostridioides difficile and carbapenem-resistant Enterobacteriaceae infection rates, along with 4 of 5 types of surgical site SIRs coincided with the periods of lowest IP staffing levels and the absence of certified IPs and a healthcare epidemiologist. Central-line–associated bloodstream infections increased amid lower nursing levels despite the increased presence of an IP and a hospital epidemiologist.
Conclusions:
Of 10 HAIs, 8 had highest incidences during periods of lowest IP staffing and experience. Some HAI rates varied inversely with levels of IP staffing and experience and others appeared to be more influenced by nursing levels or other confounders.
The distinct turbulence dynamics and transport modulated by a common seagrass species were investigated experimentally using a flexible surrogate canopy in a refractive-index-matching environment that enabled full optical access. The surrogate seagrass replicated the dynamic behaviour and morphological properties of its natural counterpart. The flows studied were subcritical with Froude numbers $Fr<0.26$ and concerned five Reynolds numbers $Re\in [3.4\times 10^{4}, 1.1\times 10^{5}]$ and Cauchy numbers $Ca\in [120, 1200]$. Complementary rigid canopy experiments were also included to aid comparative insight. The flow was quantified in wall-normal planes in a developed region using high-frame-rate particle image velocimetry. Results show that the deflection and coordinated waving motion of the blades redistributed the Reynolds stresses above and below the canopy top. Critically, in-canopy turbulence associated with the seagrass lacked periodic stem wake vortex shedding present in the rigid canopy, yet the flexible canopy induced vortex shedding from the blade tips. Inspection of spatial and temporal characteristics of coherent flow structures using spectral proper orthogonal decomposition reveals that Kelvin–Helmholtz-type vortices are the dominant flow structures associated with the waving motion of the seagrass and that modulated the local flow exchange in both rigid and flexible canopies. A barrier-like effect produced by the blade deflections blocked large-scale turbulence transport, thereby reducing vortex penetration into the canopy. In addition, we uncovered a transition from sweep-dominated to ejection-dominated behaviour in the surrogate seagrass. We hypothesise that the vortices created during the upward blade motion period play a major role in the sweep-to-ejection-dominated transition. Conditionally averaged quadrant analysis on the downward and upward blade motion supports this contention.