AgTC and AgETL: open-source tools to enhance data collection and management for plant science research.

Advancements in phenotyping technology have enabled plant science researchers to gather large volumes of information from their experiments, especially those that evaluate multiple genotypes. To fully leverage these complex and often heterogeneous data sets (i.e. those that differ in format and structure), scientists must invest considerable time in data processing, and data management has emerged as a considerable barrier for downstream application. Here, we propose a pipeline to enhance data collection, processing, and management from plant science studies comprising of two newly developed open-source programs. The first, called AgTC, is a series of programming functions that generates comma-separated values file templates to collect data in a standard format using either a lab-based computer or a mobile device. The second series of functions, AgETL, executes steps for an Extract-Transform-Load (ETL) data integration process where data are extracted from heterogeneously formatted files, transformed to meet standard criteria, and loaded into a database. There, data are stored and can be accessed for data analysis-related processes, including dynamic data visualization through web-based tools. Both AgTC and AgETL are flexible for application across plant science experiments without programming knowledge on the part of the domain scientist, and their functions are executed on Jupyter Notebook, a browser-based interactive development environment. Additionally, all parameters are easily customized from central configuration files written in the human-readable YAML format. Using three experiments from research laboratories in university and non-government organization (NGO) settings as test cases, we demonstrate the utility of AgTC and AgETL to streamline critical steps from data collection to analysis in the plant sciences.

Impact of Treatment Modality and Route of Administration on Cytokine Release Syndrome in Relapsed or Refractory Multiple Myeloma: A Meta-Analysis.

B-cell maturation antigen (BCMA)-targeting immunotherapies (e.g., chimeric antigen receptor T cells (CAR-T) and bispecific antibodies (BsAbs)) have achieved remarkable clinical responses in patients with relapsed and/or refractory multiple myeloma (RRMM). Their use is accompanied by exaggerated immune responses related to T-cell activation and cytokine elevations leading to cytokine release syndrome (CRS) in some patients, which can be potentially life-threatening. However, systematic evaluation of the risk of CRS with BCMA-targeting BsAb and CAR-T therapies, and comparisons across different routes of BsAb administration (intravenous (i.v.) vs. subcutaneous (s.c.)) have not previously been conducted. This study utilized a meta-analysis approach to compare the CRS profile in BCMA-targeting CAR-T vs. BsAb immunotherapies administered either i.v. or s.c. in patients with RRMM. A total of 36 studies including 1,560 patients with RRMM treated with BCMA-targeting CAR-T and BsAb therapies were included in the analysis. The current analysis suggests that compared with BsAbs, CAR-T therapies were associated with higher CRS incidences (88% vs. 59%), higher rates of grade ≥ 3 CRS (7% vs. 2%), longer CRS duration (5 vs. 2 days), and more prevalent tocilizumab use (44% vs. 25%). The proportion of CRS grade ≥ 3 may also be lower (0% vs. 4%) for BsAb therapies administered via the s.c. (3 studies, n = 311) vs. i.v. (5 studies, n = 338) route. This meta-analysis suggests that different types of BCMA-targeting immunotherapies and administration routes could result in a range of CRS incidence and severity that should be considered while evaluating the benefit-risk profiles of these therapies.

Positive effects of public breeding on US rice yields under future climate scenarios.

In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from historical Uniform Regional Rice Nursery trials (1980 to 2018) conducted in the same states. Finally, the ensemble model is used with forecasted weather from the Coupled Model Intercomparison Project across the 110 rice-growing counties to predict production in the coming decades for Composite Variety Groups assembled based on year of release, breeding program, and several breeding trends. Results indicate positive effects over time of public breeding on rice resilience to future climates, and potential reasons are discussed.

Optimizing Ophthalmology Patient Education via ChatBot-Generated Materials: Readability Analysis of AI-Generated Patient Education Materials and The American Society of Ophthalmic Plastic and Reconstructive Surgery Patient Brochures.

PURPOSE: This study aims to compare the readability of patient education materials (PEM) of the American Society of Ophthalmic Plastic and Reconstructive Surgery to that of PEMs generated by the AI-chat bots ChatGPT and Google Bard. METHODS: PEMs on 16 common American Society of Ophthalmic Plastic and Reconstructive Surgery topics were generated by 2 AI models, ChatGPT 4.0 and Google Bard, with and without a 6th-grade reading level prompt modifier. The PEMs were analyzed using 7 readability metrics: Flesch Reading Ease Score, Gunning Fog Index, Flesch-Kincaid Grade Level, Coleman-Liau Index, Simple Measure of Gobbledygook Index Score, Automated Readability Index, and Linsear Write Readability Score. Each AI-generated PEM was compared with the equivalent American Society of Ophthalmic Plastic and Reconstructive Surgery PEM. RESULTS: Across all readability indices, PEM generated by ChatGPT 4.0 consistently had the highest readability scores, indicating that the material generated by this AI chatbot may be most difficult to read in its unprompted form (Flesch Reading Ease Score: 36.5; Simple Measure of Gobbledygook: 14.7). Google's Bard was able to generate content that was easier to read than both the American Society of Ophthalmic Plastic and Reconstructive Surgery and ChatGPT 4.0 (Flesch Reading Ease Score: 52.3; Simple Measure of Gobbledygook: 12.7). When prompted to produce PEM at a 6th-grade reading level, both ChatGPT 4.0 and Bard were able to significantly improve in their readability scores, with prompted ChatGPT 4.0 being able to consistently generate content that was easier to read (Flesch Reading Ease Score: 67.9, Simple Measure of Gobbledygook: 10.2). CONCLUSION: This study suggests that AI tools, when guided by appropriate prompts, can generate accessible and comprehensible PEMs in the field of ophthalmic plastic and reconstructive surgeries, balancing readability with the complexity of the necessary information.

An Investigation in the Comparability of the Exposure and Recommended Dose of Selected Pfizer Drugs in East Asian Countries: Is Mutual Usage of Clinical Data Among East Asian Countries Feasible?

The current regulatory path for new drug registration in East Asian countries has led to significant delay of the new medicines in these countries. A unified regulatory path and allowance of mutual usage of clinical data in East Asian countries would lead to cost saving in drug development and expedite the new drug registration in these countries. The objectives of the present analysis are to compare the approval dates of a selection of products developed by Pfizer in the United States and East Asian countries (China, Japan, Korea) and compare the pharmacokinetics and recommended doses of these products in East Asian countries. Eighteen products (20 drugs, 2 products with 2 combination drugs) with exposure data available in at least 2 of the 3 East Asian countries across different therapeutic areas were included in the analyses. The results showed that most products had delayed approval in East Asian countries (up to 8 years) after US or EU approval. No distinct differences were observed in the drug exposure and recommended doses for the selected products in East Asian countries. These results together with literature data of genetic similarity of the East Asian populations support the mutual usage of the clinical data in the East Asian countries for expedited regulatory submission and approval.

Case-control matching-guided exposure-efficacy relationship for avelumab in patients with urothelial carcinoma.

Exposure-response (E-R) analyses are an integral component of understanding the benefit/risk profile of novel oncology therapeutics. These analyses are typically conducted using data from the treatment arm to characterize the relationship between drug exposure (low vs. high) and efficacy or safety outcomes. For example, outcomes of patients with lower exposure in the treatment arm (e.g., Q1) might be compared to outcomes of those with higher drug exposure (Q2, Q3, and Q4). Outcomes from the lowest exposure quartile may be also compared to the control arm to evaluate whether the Q1 subgroup derived clinical benefit. However, the sample size and the distribution of patient baseline characteristics and disease risk factors are not balanced in such a comparison (Q1 vs. control), which may bias the analysis and causal interpretation of clinical benefit in the Q1 subgroup. Herein, we report the use of case-control matching to account for this bias and better understand the E-R relationship for avelumab in urothelial carcinoma, a PD-L1 inhibitor approved for the treatment of several cancers. Data from JAVELIN-100 was utilized which is a phase III study of avelumab in first-line maintenance treatment in patients with urothelial carcinoma; this clinical study demonstrated superiority of avelumab versus best-supportive care leading to approval in the United States, Europe, and other countries. A post hoc case-control matching method was implemented to compare the efficacy outcome between Q1 avelumab subgroup and matched patients extracted from the control arm with similar baseline characteristics, which showed a clinically relevant difference in overall survival in favor of the Q1 avelumab subgroup. This analysis demonstrates the importance of accounting for imbalance in important baseline covariates when comparing efficacy outcomes between subgroups within the treatment arm versus the control arm.

Quantifying physiological trait variation with automated hyperspectral imaging in rice.

Advancements in hyperspectral imaging (HSI) together with the establishment of dedicated plant phenotyping facilities worldwide have enabled high-throughput collection of plant spectral images with the aim of inferring target phenotypes. Here, we test the utility of HSI-derived canopy data, which were collected as part of an automated plant phenotyping system, to predict physiological traits in cultivated Asian rice (Oryza sativa). We evaluated 23 genetically diverse rice accessions from two subpopulations under two contrasting nitrogen conditions and measured 14 leaf- and canopy-level parameters to serve as ground-reference observations. HSI-derived data were used to (1) classify treatment groups across multiple vegetative stages using support vector machines (≥ 83% accuracy) and (2) predict leaf-level nitrogen content (N, %, n=88) and carbon to nitrogen ratio (C:N, n=88) with Partial Least Squares Regression (PLSR) following RReliefF wavelength selection (validation: R 2 = 0.797 and RMSEP = 0.264 for N; R 2 = 0.592 and RMSEP = 1.688 for C:N). Results demonstrated that models developed using training data from one rice subpopulation were able to predict N and C:N in the other subpopulation, while models trained on a single treatment group were not able to predict samples from the other treatment. Finally, optimization of PLSR-RReliefF hyperparameters showed that 300-400 wavelengths generally yielded the best model performance with a minimum calibration sample size of 62. Results support the use of canopy-level hyperspectral imaging data to estimate leaf-level N and C:N across diverse rice, and this work highlights the importance of considering calibration set design prior to data collection as well as hyperparameter optimization for model development in future studies.

Challenges of clinical translation from single-cell sequencing to measures in clinical biochemistry of haematology: Definition of immune cell identities.

Peripheral immune cells play important roles in the maintenance of systemic and microenvironmental hemostasis. Measurements of circulating blood cells by single-cell RNA sequencing (scRNA-seq) were proposed as one of the routine measures in clinical biochemistry of hematology. Out of translational challenges, defining precise identities of cell subsets and states is more difficult, due to the complexity of immune cell development, location, regulation, function, and metabolism. It is also a challenge to precisely interpret clinical significance and impact of each cell identity marker gene panel (ciMGPs). ciMGPs have potential to advance the understanding of systemic responses of the disease, identify disease-specific biomarkers, and to define cell heterogeneity. Recently, a large number of peripheral cell subsets and expending/activating states have been identified and validated for use in the fast developments in clinical single cell biomedicine. Defining specificity, measurability, and repeatability of cell subsets/states is important for translation of peripheral scRNA-seq in clinical hematology and biochemistry. The development of standard operating procedure and performance of clinical trials in large populations at various ages, diseases, and therapies will promote the clinical translation of ciMGPs to measures. Thus, defining cell subset/state identities will provide the multi-dimensional and comprehensive readouts of systemic immune cells, the precision monitoring of immune dynamics, and deeper-understanding of the disease and response to therapy.

Genomic prediction and association mapping of maize grain yield in multi-environment trials based on reaction norm models.

Genotype-by-environment interaction (GEI) is among the greatest challenges for maize breeding programs. Strong GEI limits both the prediction of genotype performance across variable environmental conditions and the identification of genomic regions associated with grain yield. Incorporating GEI into yield prediction models has been shown to improve prediction accuracy of yield; nevertheless, more work is needed to further understand this complex interaction across populations and environments. The main objectives of this study were to: 1) assess GEI in maize grain yield based on reaction norm models and predict hybrid performance across a gradient of environmental (EG) conditions and 2) perform a genome-wide association study (GWAS) and post-GWAS analyses for maize grain yield using data from 2014 to 2017 of the Genomes to Fields initiative hybrid trial. After quality control, 2,126 hybrids with genotypic and phenotypic data were assessed across 86 environments representing combinations of locations and years, although not all hybrids were evaluated in all environments. Heritability was greater in higher-yielding environments due to an increase in genetic variability in these environments in comparison to the low-yielding environments. GWAS was carried out for yield and five single nucleotide polymorphisms (SNPs) with the highest magnitude of effect were selected in each environment for follow-up analyses. Many candidate genes in proximity of selected SNPs have been previously reported with roles in stress response. Genomic prediction was performed to assess prediction accuracy of previously tested or untested hybrids in environments from a new growing season. Prediction accuracy was 0.34 for cross validation across years (CV0-Predicted EG) and 0.21 for cross validation across years with only untested hybrids (CV00-Predicted EG) when compared to Best Linear Unbiased Prediction (BLUPs) that did not utilize genotypic or environmental relationships. Prediction accuracy improved to 0.80 (CV0-Predicted EG) and 0.60 (CV00-Predicted EG) when compared to the whole-dataset model that used the genomic relationships and the environmental gradient of all environments in the study. These results identify regions of the genome for future selection to improve yield and a methodology to increase the number of hybrids evaluated across locations of a multi-environment trial through genomic prediction.

Where the wild things are: genetic associations of environmental adaptation in the Oryza rufipogon species complex.

Crop wild relatives host unique adaptation strategies that enable them to thrive across a wide range of habitats. As pressures from a changing climate mount, a more complete understanding of the genetic variation that underlies this adaptation could enable broader utilization of wild materials for crop improvement. Here, we carry out environmental association analyses (EAA) in the Oryza rufipogon species complex (ORSC), the wild progenitor of cultivated Asian rice, to identify genomic regions associated with environmental adaptation characterized by variation in bioclimatic and soil variables. We further examine regions for colocalizations with phenotypic associations within the same collection. EAA results indicate that significant regions tend to associate with single environmental variables, although 2 significant loci on chromosomes 3 and 5 are detected as common across multiple variable types (i.e. precipitation, temperature, and/or soil). Distributions of allele frequencies at significant loci across subpopulations of cultivated Oryza sativa indicate that, in some cases, adaptive variation may already be present among cultivars, although evaluation in cultivated populations is needed to empirically test this. This work has implications for the potential utility of wild genetic resources in pre-breeding efforts for rice improvement.

State spaces for agriculture: A meta-systematic design automation framework.

Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In other cases, designs were deliberately chosen and implemented over decades, as during the Green Revolution. Currently, much work in the agricultural sciences focuses on evaluating designs that could improve agriculture's sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods to meet stakeholders' often semi-incompatible goals. This ad-hoc approach presents the risk that agricultural science will overlook nonobvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, to address the problem of proposing and evaluating agricultural designs computationally. This approach overcomes limitations of current agricultural system design methods by enabling a general set of computational abstractions to explore and select from a very large agricultural design space, which can then be empirically tested.

Assessment of the drug-drug interaction potential for therapeutic proteins with pro-inflammatory activities.

It is well-recognized that therapeutic proteins (TPs) with pro-inflammatory activities elevate the pro-inflammatory cytokines and result in cytokine-drug interactions. In the current review, several pro-inflammatory cytokines, including IL-2, IL-6, IFN-γ, and TNF-α, as well as an anti-inflammatory cytokine IL-10, were summarized for their respective effect on major cytochrome P450 enzymes and efflux transporter PgP. Pro-inflammatory cytokines are generally associated with suppression of CYP enzymes across assay systems but have varied effect on Pgp expression levels and activities depending on the individual cytokines and assay systems, whereas IL-10 had no significant impact on CYP enzymes and P-gp. A cocktail drug-drug interaction (DDI) study design could be an ideal approach for simultaneously assess the impact of TPs with pro-inflammatory activities on multiple CYP enzymes. Clinical DDI studies using the cocktail approach have been conducted for several TPs with pro-inflammatory activities and for those TPs with pro-inflammatory activities which had no clinical DDI study conducted, languages for potential DDI risk due to cytokine-drug interaction were included in the label. Up to date drug cocktails, including clinically validated and unvalidated for DDI assessment, were summarized in this review. Most clinically validated cocktails focused either on CYP enzymes or transporters. Additional effort was needed to validate a cocktail to include both the major CYP enzymes and key transporters. In silico methods for assessment of the DDI for TPs with pro-inflammatory activities were also discussed.

Optimizing benefit/risk in oncology: Review of post-marketing dose optimization and reflections on the road ahead.

Oncology therapies shifted from chemotherapy to molecularly targeted agents and finally to the era of immune-oncology agents. In contrast to cytotoxic agents, molecularly targeted agents are more selective, exhibit a wider therapeutic window, and may maximally modulate tumor growth at doses lower than the maximum tolerated dose (MTD). However, first-in-patient oncology studies for molecularly targeted agents continued to evaluate escalating doses using limited number of patients per dose cohort assessing dose-limiting toxicities to identify the MTD which is commonly selected for further development adopting a 'more is better' approach that led to several post-marketing requirement (PMR) studies to evaluate alternative, typically lower, doses or dosing frequencies to optimize the benefit-risk profile. In this review, post-marketing dose optimization efforts were reviewed including those required by a regulatory pathway or voluntarily conducted by the sponsor to improve efficacy, safety, or method of administration. Lessons learned and future implications from this deep dive review are discussed considering the evolving regulatory landscape on dose optimization for oncology compounds.

Regulator of Awn Elongation 3, an E3 ubiquitin ligase, is responsible for loss of awns during African rice domestication.

Two species of rice have been independently domesticated from different ancestral wild species in Asia and Africa. Comparison of mutations that underlie phenotypic and physiological alterations associated with domestication traits in these species gives insights into the domestication history of rice in both regions. Asian cultivated rice, Oryza sativa, and African cultivated rice, Oryza glaberrima, have been modified and improved for common traits beneficial for humans, including erect plant architecture, nonshattering seeds, nonpigmented pericarp, and lack of awns. Independent mutations in orthologous genes associated with these traits have been documented in the two cultivated species. Contrary to this prevailing model, selection for awnlessness targeted different genes in O. sativa and O. glaberrima. We identify Regulator of Awn Elongation 3 (RAE3) a gene that encodes an E3 ubiquitin ligase and is responsible for the awnless phenotype only in O. glaberrima. A 48-bp deletion may disrupt the substrate recognition domain in RAE3 and diminish awn elongation. Sequencing analysis demonstrated low nucleotide diversity in a ~600-kb region around the derived rae3 allele on chromosome 6 in O. glaberrima compared with its wild progenitor. Identification of RAE3 sheds light on the molecular mechanism underlying awn development and provides an example of how selection on different genes can confer the same domestication phenotype in Asian and African rice.

Intravascular Large B-cell Lymphoma Diagnosed by Nasal Biopsy in a Patient Presenting with Bilateral Ptosis and Ophthalmoplegia.

Intravascular large B-cell lymphoma (IVLBCL) is a rare type of lymphoma, involving the lumen of predominantly small blood vessels, especially capillaries. The orbit is an uncommon site of involvement for IVLBCL, and diagnosis before autopsy is even more rare as most cases are established post-mortem. Herein, the authors describe a 73-year-old male who presented with 3 weeks of progressive bilateral ptosis and ophthalmoplegia. Computed tomography (CT) and subsequent magnetic resonance imaging (MRI) revealed diffuse abnormal thickening and enhancement of bilateral orbital apices, superior orbital fissures, and cavernous sinus, along with persistent focal opacification of the left frontal and ethmoid sinuses. Infectious and inflammatory workup of serum and cerebrospinal fluid was negative. Ethmoidal sinus and middle turbinate biopsy confirmed intravascular large B-cell lymphoma and the patient was started on R-CHOP chemotherapy regimen.

Comparison of Postoperative Infection Rates After Office-based Oculoplastic Procedures Using Sterile and Clean Gloves.

PURPOSE: To compare postoperative infection (PI) rates using sterile and clean-boxed gloves in office-based oculoplastic procedures. METHODS: Prospective, comparative study of patients undergoing oculoplastic procedures by a single surgeon (RS) in an office-based procedure room between October 2018 and September 2020. Participants included were 18 years or older. Excluded were patients on oral antibiotics within 2 weeks before the procedure, had a follow-up period of less than 1 week, had a contaminated wound, had complex reconstructions, or had multiple simultaneous procedures performed. Oculoplastic procedures were performed using either sterile or clean-boxed gloves. The main outcome measure was the frequency of postoperative infection. RESULTS: Three thousand one hundred twenty-nine patients, 1,815 (58%) of whom were women, with a mean age of 60 (18-102) years were included. One thousand five hundred seventy procedures were performed with sterile gloves, while 1,559 were performed with clean-boxed gloves. The patients in the 2 groups were similar in age, gender, and number of high-risk individuals. One patient in the sterile glove group who underwent upper blepharoplasty (0.064%) and one patient (0.064%) in the clean-boxed glove group who had an external levator advancement blepharoptosis repair developed PI. Neither patient had risk factors for infection, and both infections resolved after 1 week of oral amoxicillin-clavulanate 875/125 mg twice daily. CONCLUSIONS: In minimally complex in-office oculoplastic procedures, using sterile versus clean-boxed gloves resulted in similar low infection rates in this large cohort. The healthcare benefits may not outweigh the costs of using sterile gloves universally for office-based oculoplastic procedures.

Tarsal Ectropion Repair With Modified Bick Eyelid Tightening and Inverting Sutures.

PURPOSE: The authors report on a 10-year experience of correcting tarsal ectropion using a combined method of modified Bick eyelid tightening (MBLT) and inverting sutures. METHODS: Retrospective, interventional case series of consecutive patients with tarsal ectropion who underwent MBLT and inverting sutures by a single surgeon (RS) between July 2010 and July 2020. Thirty-four patients, 24 of whom were female, with a mean age of 81.6 years (range 59-92) were included. Eight patients had bilateral disease. All procedures were performed under local anesthesia in an office setting. Treatment success was defined by eyelid position, symptoms, and need for reoperation. RESULTS: Thirty-one patients (91%) had a successful outcome. Three patients (9%) had satisfactory results with improved symptoms and mild residual ectropion, for which further surgery was not required. No patients had poor results. The mean follow-up time was 4.5 months (range 3-11 months). The inverting sutures were well tolerated in all cases and none had to be removed due to ocular surface discomfort. There were no visible scars from the inverting sutures in any patient at postoperative month 3. CONCLUSIONS: A combination of eyelid tightening using MBLT and inverting sutures is a simple and effective treatment for lower eyelid tarsal ectropion with minimal tissue dissection.

Physiological trait networks enhance understanding of crop growth and water use in contrasting environments.

Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential ("risky" stomatal regulation), high xylem hydraulic conductivity and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance and low stomatal conductance at low leaf water potential ("conservative" stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits, soil characteristics and their interactions (i.e., networks), has potential to improve our understanding of crop performance in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.