cssi/SciSciGPT-SciSciNet huggingface dataset:
Highly Efficient 8-bit Low Precision Inference of Convolutional Neural Networks with IntelCaffe

High throughput and low latency inference of deep neural networks are critical for the deployment of deep learning applications. This paper presents the efficient inference techniques of IntelCaffe, the first Intel(R) optimized deep learning framework that supports efficient 8-bit low precision inference and model optimization techniques of convolutional neural networks on Intel(R) Xeon(R) Scalable Processors. The 8-bit optimized model is automatically generated with a calibration process from FP32 model without the need of fine-tuning or retraining. We show that the inference throughput and latency with ResNet-50, Inception-v3 and SSD are improved by 1.38X-2.9X and 1.35X-3X respectively with neglectable accuracy loss from IntelCaffe FP32 baseline and by 56X-75X and 26X-37X from BVLC Caffe. All these techniques have been open-sourced on IntelCaffe GitHub (https://github.com/intel/caffe), and the artifact is provided to reproduce the result on Amazon AWS Cloud.
The deteriorating usefulness of financial report information and how to reverse it

There is a wide-spread and growing dissatisfaction with the relevance and usefulness of financial report information, particularly among investors and corporate executives. The dissatisfaction is c...
Inapproximability results for set splitting and satisfiability problems with no mixed clauses

We prove hardness results for approximating set splitting problems and also instances of satisfiability problems which have no “mixed” clauses, i.e., every clause has either all its literals unnegated or all of them negated. Results of Hastad imply tight hardness results for set splitting when all sets have size exactly $k \ge 4$ elements and also for non-mixed satisfiability problems with exactly $k$ literals in each clause for $k \ge 4$. We consider the case $k=3$. For the MAX E3-SET SPLITTING, problem in which all sets have size exactly 3, we prove an NP-hardness result for approximating within any factor better than ${\frac{19}{20}}$. This result holds even for satisfiable instances of MAX E3-SET SPLITTING, and is based on a PCP construction due to Hastad. For “non-mixed MAX 3SAT,” we give a PCP construction which is a slight variant of the one given by Hastad for MAX 3SAT, and use it to prove the NP-hardness of approximating within a factor better than ${\frac{11}{12}}$.
Compliance estimation and multiscale seismic simulation of hydraulic fractures

AbstractHydraulic fracturing is a common stimulation technique in unconventional reservoirs to create fractures systems and allow hydrocarbon production. Proppant (granular material) is normally in...
Temporal Artifacts from Edge Accumulation in Social Interaction Networks

There has been extensive research on social networks and methods for specific tasks such as: community detection, link prediction, and tracing information cascades; and a recent emphasis on using temporal dynamics of social networks to improve method performance. The underlying models are based on structural properties of the network, some of which we believe to be artifacts introduced from common misrepresentations of social networks. Specifically, representing a social network or series of social networks as an accumulation of network snapshots is problematic. In this paper, we use datasets with timestamped interactions to demonstrate how cumulative graphs differ from activity-based graphs and may introduce temporal artifacts.
Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models

We propose a new class of filtering and smoothing methods for inference in high-dimensional, nonlinear, non-Gaussian, spatio-temporal state-space models. The main idea is to combine the ensemble Ka...
State-of-the-Art and Gaps for Deep Learning on Limited Training Data in Remote Sensing

Deep learning usually requires big data, with respect to both volume and variety. However, most remote sensing applications only have limited training data, of which a small subset is labeled. Herein, we review three state-of-the-art approaches in deep learning to combat this challenge. The first topic is transfer learning, in which some aspects of one domain, e.g., features, are transferred to another domain. The next is unsupervised learning, e.g., autoencoders, which operate on unlabeled data. The last is generative adversarial networks, which can generate realistic looking data that can fool the likes of both a deep learning network and human. The aim of this article is to raise awareness of this dilemma, to direct the reader to existing work and to highlight current gaps that need solving.
DarkCapPy: Dark matter capture and annihilation

Abstract DarkCapPy is a Python 3/Jupyter package for calculating rates associated with dark matter capture in the Earth, annihilation into light mediators, and the subsequent observable decay of the light mediators near the surface of the Earth. The package includes a calculation of the Sommerfeld enhancement at the center of the Earth and the timescale for capture–annihilation equilibrium. The code is open source and can be modified for other compact astronomical objects and mediator spins. Program summary Program Title: DarkCapPy Program Files doi: http://dx.doi.org/10.17632/kkwpb5dyn9.1 Licensing provisions: MIT License Programming language: Python 3 Nature of problem: Calculate the rate at which dark matter accumulates and annihilates into light mediators in the Earth. Calculate the resulting number of signal events from light mediator decays at the IceCube Neutrino Observatory. Solution method: Python 3/Jupyter code that automates the calculation of intermediate steps and takes appropriate limits to do parameter scans in a computationally efficient manner.
The Ethnic Segregation of Immigrants in the United States from 1850 to 1940

We provide the first estimates of immigrant residential segregation between 1850 and 1940 that cover the entire United States and are consistent across time and space. To do so, we adapt the Logan–Parman method to immigrants by measuring segregation based on the nativity of the next-door neighbor. In addition to providing a consistent measure of segregation, we also document new patterns such as high levels of segregation in rural areas, in small factory towns and for non-European sources. Early twentieth-century immigrants spatially assimilated at a slow rate, leaving immigrants’ lived experience distinct from natives for decades after arrival.
Spatially Constrained Organic Diquat Anolyte for Stable Aqueous Flow Batteries

Redox-active organic materials (ROMs) are becoming increasingly attractive for use in redox flow batteries as promising alternatives to traditional inorganic counterparts. However, the reported ROMs are often accompanied by challenges, including poor solubility and stability. Herein, we demonstrate that the commonly used diquat herbicides, with solubilities of >2 M in aqueous electrolytes, can be used as stable anolyte materials in organic flow batteries. When coupled with a ferrocene-derived catholyte, the flow cells with the diquat anolyte demonstrate long galvanic cycling with high capacity retention. Notably, the mechanistic underpinnings of this remarkable stability are attributed to the improved π-conjugation that originated from the near-planar molecular conformations of the spatially constrained 2,2′-bipyridyl rings, suggesting a viable structural engineering strategy for designing stable organic materials.
High-throughput micro-phenotyping measurements applied to assess stalk lodging in maize (Zea mays L.).

The biomechanical properties of maize stalks largely determine their lodging resistance, which affects crop yield per unit area. However, the quantitative and qualitative relationship between micro-phenotypes and the biomechanics of maize stalks is still under examined. In particular, the roles of the number, geometry, and distribution of vascular bundles of stalks in maize lodging resistance remain unclear. Research on these biomechanical properties will benefit from high-resolution micro-phenotypic image acquisition capabilities, which have been improved by modern X-ray imaging devices such as micro-CT and the development of micro-phenotyping analysis software. Hence, high-throughput image analysis and accurate quantification of anatomical phenotypes of stalks are necessary. We have updated VesselParser version 1.0 to version 2.0 and have improved its performance, accuracy, and computation strategies. Anatomical characteristics of the second and third stalk internodes of the cultivars ‘Jingke968’ and ‘Jingdan38’ were analyzed using VesselParser 2.0. The relationships between lodging resistance and anatomical phenotypes of stalks between the two different maize varieties were investigated. The total area of vascular bundles in the peripheral layer, auxiliary axis diameter, and total area of vascular bundles were revealed to have the highest correlation with mechanical properties, and anatomical phenotypes of maize stalk were better predictors of mechanical properties than macro features observed optically from direct measurement, such as diameter and perimeter. This study demonstrates the utility of VesselParser 2.0 in assessing stalk mechanical properties. The combination of anatomical phenotypes and mechanical behavior research provides unique insights into the problem of stalk lodging, showing that micro phenotypes of vascular bundles are good predictors of maize stalk mechanical properties that may be important indices for the evaluation and identification of the biomechanical properties to improve lodging resistance of future maize varieties.
Field size effects on the risk and severity of treatment-induced lymphopenia in patients undergoing radiation therapy for solid tumors.

Abstract Purpose Radiation-induced lymphopenia (RIL) is the result of direct toxicity to circulating lymphocytes as they traverse the irradiated field, occurs in 40% to 70% of patients who undergo conventional external beam radiation therapy, and is associated with worse outcomes in multiple solid tumors. As immunotherapy strategies evolve, a better understanding of radiation's effects on the immune system is needed in order to develop rational methods of combining RT with immunotherapy. Methods and materials This paper is a review of the available literature on the clinical significance and dosimetric predictors of radiation-induced toxicity to the immune system. Results An association between severe RIL and inferior survival has been described in multiple solid tumors, including glioma, lung cancer, and pancreatic cancer. RIL risk is correlated with field size, dose per fraction, and fraction number. SBRT and proton therapy techniques are associated with lower RIL risk. Conclusions The immune system should be considered an organ at risk during RT, and absolute lymphocyte count is an important biomarker of RT-induced immunotoxicity. Radiation dose and technique affect the risk and severity of RIL. Further research is needed to accurately characterize RT-induced immunotoxicity and develop strategies to prevent or mitigate this clinically significant side effect.
Magnetocardiographic study of patients with right and left bundle branch blocks

Abstract It has been recently proposed that magnetocardiographic mapping (MCG) can be useful for early diagnosis of IHD also in patients with LBBB; however, MCG patterns of cBBB in the absence of IHD have not so far extensively investigated. This study was aimed to define typical magnetic field distribution (MFD) patterns and several quantitative parameters of ventricular depolarization (QRS) and repolarization (VR), in patients with cBBB. 38 patients (pts) with cBBB at the ECG [15 RBBB, 19 LBBB, 4 RBBB + LAH] and 33 healthy subjects (HS) were consecutively investigated with an unshielded 36-channels DC SQUID MCG system (sensitivity is 20 fT/Hza1/2, above 1 Hz). Quantitative analysis of MFD maps was automatically performed during the QRS and VR intervals. In RBBB pts, the direction of septal depolarization was normal. A significant (p
Unilateral tax reform: Border adjusted taxes, cash flow taxes, and transfer pricing

Abstract We study the economic effects of unilateral adoption of corporate tax policies that include the choice between destination-based and source-based taxation and between cash flow and income taxes. We utilize a heterogeneous firm model in which monopolistically competitive North firms choose whether to outsource an intermediate good to an unrelated South firm or to produce in a subsidiary in the South. Standard pass through arguments no longer apply because of the income shifting behavior of multinationals and endogenous choice of organizational form. The high tax North country will prefer a destination-based tax over a source-based tax if it adopts a cash flow tax, but whether the cash flow tax is preferred to an income tax will depend on the volume of trade in the differentiated products sector. If the high tax country adopts a destination-based cash flow tax, the low tax country will prefer a destination-based income tax to capture rents from the foreign subsidiaries.
How do Capital Requirements Affect Loan Rates? Evidence from High Volatility Commercial Real Estate

We study how bank loan rates responded to a 50% increase in capital requirements for a subcategory of construction lending, High Volatility Commercial Real Estate (HVCRE). To identify this effect, we exploit variation in the loan terms determining whether a loan is classified as HVCRE and the time that a treated loan would be subject to the increased capital requirements. We estimate that the HVCRE rule increases loan rates by about 40 basis points for HVCRE loans, indicating that a one percentage point increase in required capital raises loan rates by about 9.5 basis points.
Long-term Effects from Early Exposure to Research: Evidence from the NIH "Yellow Berets''

Abstract Can a relatively short but intense exposure to frontier research alter the career trajectories of potential innovators? To answer this question, we study the careers and productivity of 3075 medical school graduates who applied to the Associate Training Programs (ATP) of the National Institutes of Health (NIH) during the turbulent period of the Vietnam War, 1965–1975. Carefully selecting on observables, we compare physicians who attended the program to those who passed a first admission screen but were ultimately not selected. We find that program participants were twice as likely to choose a research-focused position after training, and considerably less likely to switch to purely clinical endeavors as their careers unfolded. Over the life cycle, NIH trainees also garnered publications, citations, and grant funding at a much higher rate than synthetic controls, and went on to mentor more trainees who themselves became successful researchers. The direction of their research efforts was durably imprinted by their training experience. In particular, NIH trainees appear to have acquired a distinct “translational” style of biomedical research which became an implicit training model for physician-scientists as ATP alumni came to occupy the commanding heights of academic medicine throughout the United States.
Quasirandom permutations

Chung and Graham (J. Combin. Theory Ser. A 61 (1992) 64) define quasirandom subsets of Zn to be those with any one of a large collection of equivalent random-like properties. We weaken their definition and call a subset of Zn e-balanced if its discrepancy on each interval is bounded by en. A quasirandom permutation, then, is one which maps each interval to a highly balanced set. In the spirit of previous studies of quasirandomness, we exhibit several random-like properties which are equivalent to this one, including the property of containing (approximately) the expected number of subsequences of each order-type. We present a construction for a family of strongly quasirandom permutations, and prove that this construction is essentially optimal, using a result of Schmidt on the discrepancy of sequences of real numbers.
Economic burden of renal cell carcinoma among older adults in the targeted therapy era.

Abstract Objective This study examined the economic burden of renal cell carcinoma (RCC) among older adults. The study also examined healthcare costs by types of resources used and stage at which RCC was diagnosed. Methods The study analyzed the Surveillance Epidemiology and End Result—Medicare linked data. We included a prevalent cohort of RCC patients from 2013, diagnosed and continuously enrolled in Medicare from 2005 to 2013. RCC patients were matched to controls selected from a 5% sample of noncancer beneficiaries using propensity score matching to calculate incremental costs. Total healthcare costs (THC) were calculated using a phase-based approach, which classified patients into early, continuing, and late phases of care. Costs were also examined by types of resources used and stage at which RCC was diagnosed. Generalized linear models estimated annual incremental costs per patient. The number of older RCC patients was calculated using SEER-Stat and ProjPrev software. The average incremental THC was multiplied by the estimated number of RCC patients to calculate the total economic burden of RCC among older adults. Results The study included 10,392 each of RCC and control patients. The average annual THC associated with RCC was $7,419 for all phases, $22,752 for the initial phase, $4,860 for the continuing phase, and $13,232 for the late phase of care. The average THC was $4,584 for patients diagnosed at stage I, $4,727 for stage II, $9,331 for stage III, and $31,637 for stage IV. For patients diagnosed at stages I to III, hospital cost (approximately $1,500–$3,400) was the largest component of THC. For stage IV patients, prescription drug cost ($11,747) was the largest component of THC. The projected number of older RCC patients in 2015 was 204,256. The annual economic burden of RCC after weighting for proportion of patients diagnosed at various stages was estimated to be $2.1 billion. Conclusions RCC was associated with a significant economic burden on Medicare. Healthcare costs associated with RCC varied substantially between early stage and metastatic patients. This research provided a baseline that can be used to assess the economic value of emerging therapies among older RCC patients.
The Use of Computer Decision Support for Pediatric Obstructive Sleep Apnea Detection in Primary Care.

Study Objectives:To (1) describe outcomes from a computer decision support system (CDSS) for pediatric obstructive sleep apnea (OSA) detection in primary care; and (2) identity the prevalence of ch...
Crowded Trades: Implications for Sector Rotation and Factor Timing

Crowded trades are often associated with bubbles. If investors can locate a bubble sufficiently early, they can profit from the run-up in prices. But to profit from a bubble, investors must exit the bubble before the sell-off erodes all of the profits. The authors propose two measures for managing exposure to bubbles. One measure, called asset centrality, locates crowded trading, which they show is often associated with the formation of bubbles. The other is a measure of relative value, which helps to separate crowding that occurs during a bubble’s run-up from crowding that occurs during a bubble’s sell-off. Neither measure by itself is sufficient for identifying the full cycle of a bubble, but the authors show that together these measures have the potential to locate bubbles in sectors and in factors as they begin to emerge and to identify exit points before they fully deflate. TOPICS:Portfolio construction, factors, risk premia, risk management
College internships, tenure gaps, and student outcomes: a multiple-treatment matching approach

College internships are popular and often promoted. Quantifying their impacts is difficult as students often take time away from classes to participate. We implement multiple-treatment propensity s...
The RNA-binding protein FUS/TLS undergoes calcium-mediated nuclear egress during excitotoxic stress and is required for GRIA2 mRNA processing

Excitotoxic levels of glutamate represent a physiological stress that is strongly linked to amyotrophic lateral sclerosis (ALS) and other neurological disorders. Emerging evidence indicates a role for neurodegenerative disease-linked RNA-binding proteins (RBPs) in the cellular stress response. However, the relationships between excitotoxicity, RBP function, and disease have not been explored. Here, using primary cortical and motor neurons, we found that excitotoxicity induced the translocation of select ALS-linked RBPs from the nucleus to the cytoplasm within neurons. RBPs affected by excitotoxicity included TAR DNA-binding protein 43 (TDP-43) and, most robustly, fused in sarcoma/translocated in liposarcoma (FUS/TLS or FUS). We noted that FUS is translocated through a calcium-dependent mechanism and that its translocation coincides with striking alterations in nucleocytoplasmic transport. Furthermore, glutamate-induced up-regulation of glutamate ionotropic receptor α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type subunit 2 (GRIA2) in neurons depended on FUS expression, consistent with a functional role for FUS in excitotoxic stress. These findings reveal molecular links among prominent factors in neurodegenerative diseases, namely excitotoxicity, disease-associated RBPs, and nucleocytoplasmic transport.
The Causal Effect of Service Satisfaction on Customer Loyalty

We propose an instrumental-variable (IV) approach to estimate the causal effect of service satisfaction on customer loyalty by exploiting a common source of randomness in the assignment of service ...
A tandem decarboxylation and inverse electron-demand Diels–Alder reaction of amino-thiophenecarboxylic acids with 1,3,5-triazines

Abstract The scope of 1,3,5-triazine inverse electron-demand Diels–Alder (IDA) reactions was expanded to include aminothiophenecarboxylic acids as latent dienophiles. A series of 2-amino-3-thiophenecarboxylic acids ( 1a – d ) and a 3-amino-2-thiophenecarboxylic acid ( 5 ) were introduced as productive dienophiles in IDA reactions with various 1,3,5-triazines ( 2a – e ). This method is useful for the one-step synthesis of both thieno[2,3- d ]pyrimidines and thieno[3,2- d ]pyrimidines, which should complement existing methods.
Deep-learning based, automated segmentation of macular edema in optical coherence tomography

Evaluation of clinical images is essential for diagnosis in many specialties. Therefore the development of computer vision algorithms to help analyze biomedical images will be important. In ophthalmology, optical coherence tomography (OCT) is critical for managing retinal conditions. We developed a convolutional neural network (CNN) that detects intraretinal fluid (IRF) on OCT in a manner indistinguishable from clinicians. Using 1,289 OCT images, the CNN segmented images with a 0.911 cross-validated Dice coefficient, compared with segmentations by experts. Additionally, the agreement between experts and between experts and CNN were similar. Our results reveal that CNN can be trained to perform automated segmentations of clinically relevant image features.
Homomorphic Encryption with CCA Security.

We address the problem of constructing public-key encryption schemes that meaningfully combine useful computability features with non-malleability. In particular, we investigate schemes in which anyone can change an encryption of an unknown message m into an encryption of T (m) (as a feature), for a specific set of allowed functions T , but the scheme is “non-malleable” with respect to all other operations. We formulate precise definitions that capture these intuitive requirements and also show relationships among our new definitions and other more standard ones (IND-CCA, gCCA, and RCCA). We further justify our definitions by showing their equivalence to a natural formulation of security in the Universally Composable framework. We also consider extending the definitions to features which combine multiple ciphertexts, and show that a natural definition is unattainable for a useful class of features. Finally, we describe a new family of encryption schemes that satisfy our definitions for a wide variety of allowed transformations T , and which are secure under the standard Decisional Diffie-Hellman (DDH) assumption. ∗An extended abstract of this work appears in Automata, Languages and Programming, 35th International Colloquium, ICALP 2008, Springer-Verlag, 2008. This full version is available from http://eprint.iacr.org/2008/079. †Department of Computer Science, University of Illinois, Urbana-Champaign. {mmp,rosulek}@uiuc.edu. Partially supported by NSF grant CNS 07-47027.
Simple conversion of fully protected amino acids to zwitterions

Abstract An operationally simple and efficient method under mild acidic conditions was developed to convert fully protected amino acids to the corresponding zwitterions without either isoelectric precipitation or ion exchange chromatography.
TiCl4 mediated preparation of (E)-non-conjugated homoallylic alcohols with α-substituted allylsilanes

Abstract The allylation of various aldehydes with α-substituted allylsilanes in the presence of TiCl4 has been investigated. It has been shown that these reagents readily allow for good yields and high to excellent diastereoselectivities (up to >20:1) for a series of aldehydes, thereby providing a means of preparing non-conjugated (E)-homoallylic alcohols in a single step.
Synthesis and characterization of 1-chloro-3-methylenecyclopropene

Abstract 1-Chloro-3-methylenecyclopropene was prepared by vacuum gas-solid elimination of 2,2-dichloro-1-methylene-3-(trimethylsilyl)cyclopropane over solid cesium fluoride and characterized by 1 H and 13 C NMR spectroscopy at −103 °C.
Extent of the annual Gulf of Mexico hypoxic zone influences microbial community structure

Rich geochemical datasets generated over the past 30 years have provided fine-scale resolution on the northern Gulf of Mexico (nGOM) coastal hypoxic (≤ 2 mg of O2 L-1) zone. In contrast, little is known about microbial community structure and activity in the hypoxic zone despite the implication that microbial respiration is responsible for forming low dissolved oxygen (DO) conditions. Here, we hypothesized that the extent of the hypoxic zone is a driver in determining microbial community structure, and in particular, the abundance of ammonia-oxidizing archaea (AOA). Samples collected across the shelf for two consecutive hypoxic seasons in July 2013 and 2014 were analyzed using 16S rRNA gene sequencing, oligotyping, microbial co-occurrence analysis, and quantification of thaumarchaeal 16S rRNA and archaeal ammonia-monooxygenase (amoA) genes. In 2014 Thaumarchaeota were enriched and inversely correlated with DO while Cyanobacteria, Acidimicrobiia, and Proteobacteria where more abundant in oxic samples compared to hypoxic. Oligotyping analysis of Nitrosopumilus 16S rRNA gene sequences revealed that one oligotype was significantly inversely correlated with DO in both years. Oligotyping analysis revealed single nucleotide variation among all Nitrosopumilaceae, including Nitrosopumilus 16S rRNA gene sequences, with one oligotype possibly being better adapted to hypoxia. We further provide evidence that in the hypoxic zone of both year 2013 and 2014, low DO concentrations and high Thaumarchaeota abundances influenced microbial co-occurrence patterns. Taken together, the data demonstrated that the extent of hypoxic conditions could potentially drive patterns in microbial community structure, with two years of data revealing the annual nGOM hypoxic zone to be emerging as a low DO adapted AOA hotspot.
ADAGE signature analysis: differential expression analysis with data-defined gene sets.

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http:// ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed ADAGE signature analysis to perform gene set analysis using data-defined functional gene signatures. This approach addresses an important gap for biologists studying non-traditional model organisms and those without extensive curated resources available. We built both an R package and web server to provide ADAGE signature analysis to the community.
Aldehyde dehydrogenase-mediated cellular relative insensitivity to the oxazaphosphorines.

As judged by findings in preclinical models, determinants of cellular sensitivity to cyclophosphamide and other oxazaphosphorines include two cytosolic aldehyde dehydrogenases, viz., ALDH1A1 and ALDH3A1. Each catalyzes the detoxification of the oxazaphosphorines; thus, cellular sensitivity to these agents decreases as cellular levels of ALDH1A1 and/or ALDH3A1 increase. Of particular clinical relevance may be that stable sublines, relatively insensitive to the oxazaphosphorines due to elevated ALDH1A1 or ALDH3A1 levels, emerged when cultured human tumor cells were exposed only once to a high concentration of one of these agents for 30 to 60 minutes. Whether differences in cellular levels of either enzyme accounts for the clinically-encountered uneven therapeutic effectiveness of the oxazaphosphorines remains to be determined. However, it has already been established that measurable levels of these enzymes are found in some, but not all, tumor types, and that in those tumor types where measurable levels are present, e.g., infiltrating ductal carcinomas of the breast, they vary widely from patient to patient. Potentially useful clinical strategies that might be pursued if it turns out that ALDH1A1 and/or ALDH3A1 are, indeed, clinically operative determinants of cellular sensitivity to the oxazaphosphorines include 1) individualizing cancer chemotherapeutic regimens based, at least in part, on the levels of these enzymes in the malignancy of interest, and 2) sensitizing tumor cells that express relatively large amounts of ALDH1A1 and/or ALDH3A1 to the oxazaphosphorines by preventing the synthesis of these enzymes, e.g., with antisense RNA, or by introducing an agent that directly inhibits the catalytic action of the operative enzyme. Further, the fact that ALDH1A1 and ALDH3A1 are determinants of cellular sensitivity to the oxazaphosphorines provides the rationale for the investigation of two additional strategies with clinical potential, viz., decreasing the sensitivity of vulnerable and essential normal cells, e.g., pluripotent hematopoietic cells, to the oxazaphosphorines by selectively transferring into them the genetic information that encodes 1) ALDH1A1 or ALDH3A1, or 2) a signaling factor, the presence of which would directly or indirectly, stably upregulate the expression of these enzymes.
Practical synthesis of the calcimimetic agent, cinacalcet

A practical synthesis of cinacalcet (Sensipar®, Mimpara®) is described. The synthesis starts from readily available starting materials and relies on safe and practical reaction conditions. The sequence comprises three synthetic steps and only one isolation point. The overall yield for the sequence is 85%.
Toward the synthesis of amphidinolide P: optimization of a model ene–yne metathesis fragment coupling

Abstract Ene–yne cross metathesis was assessed for use as a key fragment coupling in a planned total synthesis of amphidinolide P. A terminal alkyne containing a β,γ-epoxide was synthesized and employed as the alkyne partner in an intermolecular ene–yne metathesis. In the alkene substrate, optimal functionality and reaction conditions were determined. An unprotected allyl alcohol was found to be critical for both high yield and high E-selectivity. Fewer equivalents of the alkene resulted in incomplete reaction and side reactions consumed the terminal alkyne. The best ruthenium carbene precatalysts were found to be the Hoveyda–Grubbs carbene complexes.
Enantiospecific formal total synthesis of (+)-fawcettimine.

The diastereospecific attack of the silyl enol ether on the activated cyclopropyl diester 27 generated the hydrindanone 28 with complete stereocontrol. Thermal decarbomethoxylation of 28 gave the monoester 29, a key intermediate in Heathcock’s synthesis, thereby completing a formal total synthesis of (+)-fawcettimine 1. The analogous cyclization of 33, the diastereomer of 27, afforded the diastereomeric diester 34, thereby demonstrating that the cyclization process is diastereospecific.
A mus-51 RIP allele for transformation of Neurospora crassa

This report describes the construction and characterization of mus-51RIP70 , an allele for high-efficiency targeted integration of transgenes into the genome of the model eukaryote Neurospora crassa. Two of the mus-51RIP70 strains investigated in this work (RZS27.10 and RZS27.18) can be obtained from the Fungal Genetics Stock Center. The two deposited strains are, to our knowledge, genetically identical and neither one is preferred over the other for use in Neurospora research.
A modular approach to the synthesis of 1,4,5-substituted-2-aminoimidazoles

Abstract Diversified 1,4,5-substituted-2-aminoimidazoles were rapidly assembled via sequential N–H insertion and Grignard addition to α-diazoesters. Lead compounds were identified as antibiotics against Gram-positive bacteria with an MIC value as low as 2 μg/mL.
Synthesis of novel biaryl 2-benzimidazoles and 2-benzothiazoles

Herein, we describe the synthesis of the novel 4-(1H-benzo[d]imidazol-2-yl)isoxazol-5-amine (7) and 4-(1H-benzo[d]thiazol-2-yl)isoxazol-5-amine scaffolds (8). Initial attempts following literature procedures for the synthesis of similar compounds did not yield the desired product. Instead we obtained the ring-opened adduct 2-(1H-benzo[d]imidazol-2(3H)-ylidene)-2-cyanoacetamide (5). We were able to modify reaction conditions and successfully synthesize the desired product. We also describe a convenient one-pot microwave-assisted relay reaction for the synthesis of novel and reported 2-substituted benzimidazoles and benzothiazoles from inexpensive, commercially available reagents, 2-benzothiazole acetonitrile (2) and 2-benzimidazole acetonitrile (1). In all cases, good yields of products were obtained and reaction times were significantly reduced.
Total structure determination of grassypeptolide, a new marine cyanobacterial cytotoxin.

A collection of the cyanobacterium Lyngbya confervoides off Grassy Key in Florida yielded grassypeptolide (1), a 31-membered macrocyclic depsipeptide with unusually high d-amino acid content, two thiazolines, and one β-amino acid. We report the rigorous 3D structure determination and conformational analysis in solution and solid state by NMR, MS, X-ray crystallography, chemical degradation, and molecular modeling involving distance geometry and restrained molecular dynamics. Grassypeptolide (1) inhibited cancer cell growth with IC50 values from 1.0 to 4.2 μM.
[(E)-γ-(Dimethylphenylsilyl)allyl]diisopinocampheylborane: a highly enantioselective reagent for the synthesis of anti-β-hydroxyallylsilanes

Abstract anti -β-Hydroxyallylsilanes are prepared with 88–95% e.e. via the asymmetric allylboration reactions of aldehydes and [( E )-γ-(dimethylphenylsilyl)allyl]diisopinocampheylborane ( 7 ).
α-Proteobacterial RNA Degradosomes Assemble Liquid-Liquid Phase-Separated RNP Bodies.

Summary Ribonucleoprotein (RNP) granules play an important role in organizing eukaryotic mRNA metabolism via liquid-liquid phase separation (LLPS) of mRNA decay factors into membrane-less organelles in the cytoplasm. Here we show that the bacterium Caulobacter crescentus Ribonuclease (RNase) E assembles RNP LLPS condensates that we term bacterial RNP-bodies (BR-bodies), similar to eukaryotic P-bodies and stress granules. RNase E requires RNA to assemble a BR-body, and disassembly requires RNA cleavage, suggesting BR-bodies provide localized sites of RNA degradation. The unstructured C-terminal domain of RNase E is both necessary and sufficient to assemble the core of the BR-body, is functionally conserved in related α-proteobacteria, and influences mRNA degradation. BR-bodies are rapidly induced under cellular stresses and provide enhanced cell growth under stress. To our knowledge, Caulobacter RNase E is the first bacterial protein identified that forms LLPS condensates, providing an effective strategy for subcellular organization in cells lacking membrane-bound compartments.
Highly Functionalized Cyclohexenyl Systems: Enzymatic Resolution and Selective Oxirane Opening Reactions of p-Benzoquinone Derivatives

Diol 2, derived in two steps from p-benzoquinone, was converted to epoxy alcohol 3. The latter was resolved with crude Candida rugosa lipase in isopropenyl acetate/toluene to give acetate (−)-4 and residual alcohol (+)-3. Oxirane ring opening reactions of 3 and the corresponding acetate and TBDMS derivatives with a variety of nucleophiles gave diastereomerically pure 3,4,5,6-tetrasubstituted cyclohexene derivatives of type 6. X-ray crystal structures were obtained on compounds 6e, 6m and the diacetate prepared from 6l. Nitrogen nucleophiles provided entry in various aziridines 10. Pd(0)-catalyzed nucleophilic additions to substrate 5 cleanly provided the diastereomeric pattern of type 11. trans-5,6-Disubstituted cyclohexadienes 13 were obtained by an unusual syn-reductive elimination on bromocarbonates 12 utilizing Pd or Zn.
A framework for data-based turbulent combustion closure: A posteriori validation

Abstract In this work, we demonstrate a framework for developing closure models in turbulent combustion using experimental multi-scalar measurements. The framework is based on the construction of conditional means and joint scalar PDFs from experimental data based on the parameterization of the composition space using principal component analysis (PCA). The resulting principal components (PCs) act as both conditioning variables and transported variables. Their chemical source terms are constructed starting from instantaneous temperature and species measurements using a variant of the pairwise mixing stirred reactor (PMSR) approach. A multi-dimensional kernel density estimation (KDE) approach is used to construct the joint PDFs in PC space. Convolutions of these joint PDFs with conditional means are used to determine the unconditional means for the closure terms: the mean PCs chemical source terms and the density. These means are parameterized in terms of the mean PCs using artificial neural networks (ANN). The framework is demonstrated a posteriori using the data from the Sandia piloted turbulent jet flames D, E and F by performing RANS calculations. The radial profiles of mean and RMS of temperature and measured species mass fractions agree well with the experimental means for these flames.
Daisy-chain gene drives for the alteration of local populations.

If they are able to spread in wild populations, CRISPR-based gene-drive elements would provide new ways to address ecological problems by altering the traits of wild organisms, but the potential for uncontrolled spread tremendously complicates ethical development and use. Here, we detail a self-exhausting form of CRISPR-based drive system comprising genetic elements arranged in a daisy chain such that each drives the next. “Daisy-drive” systems can locally duplicate any effect achievable by using an equivalent self-propagating drive system, but their capacity to spread is limited by the successive loss of nondriving elements from one end of the chain. Releasing daisy-drive organisms constituting a small fraction of the local wild population can drive a useful genetic element nearly to local fixation for a wide range of fitness parameters without self-propagating spread. We additionally report numerous highly active guide RNA sequences sharing minimal homology that may enable evolutionarily stable daisy drive as well as self-propagating CRISPR-based gene drive. Especially when combined with threshold dependence, daisy drives could simplify decision-making and promote ethical use by enabling local communities to decide whether, when, and how to alter local ecosystems.
Synthesis and some transformations of 5-benzotriazolyl-3,4-dihydropyrid-2-ones

5-(Benzotriazolyl)-substituted 3,4-dihydropyrid-2-ones were obtained by condensation of 4-benzo-triazolyl-5-phenyl(methyl)-5-oxopentanoic acids with benzyl or aryl amines. Dehydrogenation of 3,4-dihydropyrid-2-ones resulted in 5-benzotriazolyl-substituted pyrid-2-ones and/or 5-(phenylamino)pyrid-2-ones, products of nitrogen elimination from the benzotriazolyl substituent. In turn, 5-benzotriazol-1-yl-substituted pyrid-2-ones eliminated nitrogen under Graebe-Ullmann conditions to give indolopyridones.
Synthesis and Characterization of New Iron and Zinc Phosphate Materials with Open Framework

Open framework materials are of great interest due to the applications in the fields of adsorption, ion exchange, molecular sieving and catalysis. Metal phosphates are very important open framework materials due to the rich crystallography. Several new iron phosphate materials have been synthesized and characterized in our lab. Two new iron (III) phosphates, FePO4, have been synthesized from careful dehydration of hydrothermally prepared monoclinic and orthorhombic hydrated phosphates FePO4·2H2O. Reversible insertion and extraction of lithium into new iron phosphate hydroxide materials with 3-d rod-packing framework shows it to be an excellent intercalation material. Several other transition metals are also incorporated successfully into these compounds without changing the structure. With ethylenediamine as template, 1-D chain, 2-D layered and 3-D network iron phosphate materials were synthesized. The structure, electrochemical and magnetic properties of these compounds were studied. Meanwhile, two new zinc phosphates with methylammonium templates were also synthesized. There are infinite Zn-O-Zn chains in one of the compounds, while closed 4-member circuits made up from Zn-O-Zn linkage present in the other.
A 2.08 Å resolution structure of HLB5, a novel cellulase from the anaerobic gut bacterium Parabacteroides johnsonii DSM 18315.

Cellulases play a significant role in the degradation of complex carbohydrates. In the human gut, anaerobic bacteria are essential to the well-being of the host by producing these essential enzymes that convert plant polymers into simple sugars that can then be further metabolized by the host. Here, we report the 2.08 A resolution structure of HLB5, a chemically verified cellulase that was identified previously from an anaerobic gut bacterium and that has no structural cellulase homologues in PDB nor possesses any conserved region typical for glycosidases. We anticipate that the information presented here will facilitate the identification of additional cellulases for which no homologues have been identified to date and enhance our understanding how these novel cellulases bind and hydrolyze their substrates.
The Evolutionary Dynamics of the Odorant Receptor Gene Family in Corbiculate Bees

Insects rely on chemical information to locate food, choose mates, and detect potential predators. It has been hypothesized that adaptive changes in the olfactory system facilitated the diversification of numerous insect lineages. For instance, evolutionary changes of Odorant Receptor (OR) genes often occur in parallel with modifications in life history strategies. Corbiculate bees display a diverse array of behaviors that are controlled through olfaction, including varying degrees of social organization, and manifold associations with floral resources. Here we investigated the molecular mechanisms driving the evolution of the OR gene family in corbiculate bees in comparison to other chemosensory gene families. Our results indicate that the genomic organization of the OR gene family has remained highly conserved for ∼80 Myr, despite exhibiting major changes in repertoire size among bee lineages. Moreover, the evolution of OR genes appears to be driven mostly by lineage-specific gene duplications in few genomic regions that harbor large numbers of OR genes. A selection analysis revealed that OR genes evolve under positive selection, with the strongest signals detected in recently duplicated copies. Our results indicate that chromosomal translocations had a minimal impact on OR evolution, and instead local molecular mechanisms appear to be main drivers of OR repertoire size. Our results provide empirical support to the longstanding hypothesis that positive selection shaped the diversification of the OR gene family. Together, our results shed new light on the molecular mechanisms underlying the evolution of olfaction in insects.
Predictive model identifies strategies to enhance TSP1-mediated apoptosis signaling

Thrombospondin-1 (TSP1) is a matricellular protein that functions to inhibit angiogenesis. An important pathway that contributes to this inhibitory effect is triggered by TSP1 binding to the CD36 receptor, inducing endothelial cell apoptosis. However, therapies that mimic this function have not demonstrated clear clinical efficacy. This study explores strategies to enhance TSP1-induced apoptosis in endothelial cells. In particular, we focus on establishing a computational model to describe the signaling pathway, and using this model to investigate the effects of several approaches to perturb the TSP1-CD36 signaling network. We constructed a molecularly-detailed mathematical model of TSP1-mediated intracellular signaling via the CD36 receptor based on literature evidence. We employed systems biology tools to train and validate the model and further expanded the model by accounting for the heterogeneity within the cell population. The initial concentrations of signaling species or kinetic rates were altered to simulate the effects of perturbations to the signaling network. Model simulations predict the population-based response to strategies to enhance TSP1-mediated apoptosis, such as downregulating the apoptosis inhibitor XIAP and inhibiting phosphatase activity. The model also postulates a new mechanism of low dosage doxorubicin treatment in combination with TSP1 stimulation. Using computational analysis, we predict which cells will undergo apoptosis, based on the initial intracellular concentrations of particular signaling species. This new mathematical model recapitulates the intracellular dynamics of the TSP1-induced apoptosis signaling pathway. Overall, the modeling framework predicts molecular strategies that increase TSP1-mediated apoptosis, which is useful in many disease settings.