Large Basket Research Articles

Widespread Adoption of Precision Anticancer Therapies After Implementation of Pathologist-Directed Comprehensive Genomic Profiling Across a Large US Health System.

Precision therapies and immunotherapies have revolutionized cancer care, with novel genomic biomarker-associated therapies being introduced into clinical practice rapidly, resulting in notable gains in patient survival. Despite this, there is significant variability in the utilization of tumor molecular profiling that spans the timing of test ordering, comprehensiveness of gene panels, and clinical decision support through therapy and trial recommendations. To standardize testing, we designed a pathologist-directed test ordering system at the time of diagnosis using a 523-gene DNA/RNA hybrid comprehensive genomic profiling (CGP) panel and extensive clinical decision support tools. To comprehensively characterize the clinical impact of this protocol, we developed a novel natural language processing (NLP)-based approach to extract clinical features from physician chart notes. We assessed test actionability rates, therapy choice, and outcomes across a set of 3,216 patients with advanced cancer. We observed 49% of patients had at least one actionable genomic biomarker-driven-approved and/or guideline-recommended targeted or immunotherapy (IO) and 53% of patients would have been eligible for a precision therapy clinical trial from three large basket trials. When assessing CGP versus an in silico 50-gene panel, 67% of tumors compared with 33% harbored actionable alterations including clinical trials. Among patients with 6 months or more of follow-up, over 52% received a targeted therapy (TT) or IO, versus 32% who received conventional chemotherapy alone. Furthermore, patients receiving TT had significantly improved overall survival compared with patients receiving chemotherapy alone (P < .001). Overall, these data represent a major shift in standard clinical practice toward molecularly guided treatments (targeted and immunotherapies) over conventional systemic chemotherapy. As guidelines continue to evolve and more precision therapeutics gain approval, we expect this gap to continue to widen.

Modulation of large rhythmic depolarizations in human large basket cells by norepinephrine and acetylcholine

Rhythmic brain activity is critical to many brain functions and is sensitive to neuromodulation, but so far very few studies have investigated this activity on the cellular level in vitro in human brain tissue samples. This study reveals and characterizes a novel rhythmic network activity in the human neocortex. Using intracellular patch-clamp recordings of human cortical neurons, we identify large rhythmic depolarizations (LRDs) driven by glutamate release but not by GABA. These LRDs are intricate events made up of multiple depolarizing phases, occurring at ~0.3 Hz, have large amplitudes and long decay times. Unlike human tissue, rat neocortex layers 2/3 exhibit no such activity under identical conditions. LRDs are mainly observed in a subset of L2/3 interneurons that receive substantial excitatory inputs and are likely large basket cells based on their morphology. LRDs are highly sensitive to norepinephrine (NE) and acetylcholine (ACh), two neuromodulators that affect network dynamics. NE increases LRD frequency through β-adrenergic receptor activity while ACh decreases it via M4 muscarinic receptor activation. Multi-electrode array recordings show that NE enhances and synchronizes oscillatory network activity, whereas ACh causes desynchronization. Thus, NE and ACh distinctly modulate LRDs, exerting specific control over human neocortical activity.

Directional sensitivity of cortical neurons towards TMS-induced electric fields

Abstract We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 245 small, nested, and large basket cells from layer 4, and 30 PC from layer 5 with different morphologies for deriving average models. With these models, it is possible to efficiently estimate the stimulation thresholds depending on the underlying electric field distribution in the brain, without having to implement and compute complex neuron compartment models. The stimulation thresholds were determined by exposing the neurons to TMS-induced electric fields with different angles, intensities, pulse waveforms, and field decays along the somato-dendritic axis. The derived average response models were verified by reference simulations using a high-resolution realistic head model containing several million neurons. The relative errors of the estimated thresholds between the average model and the reference model ranged between -3% and 3.7% in 98% of the cases, while the computation time was only a fraction of a second compared to several weeks. Finally, we compared the model behavior to TMS experiments and observed high correspondence to the orientation sensitivity of motor evoked potentials. The derived models were compared to the classical cortical column cosine model and to simplified ball-and-stick neurons. It was shown that both models oversimplify the complex interplay between the electric field and the neurons and do not adequately represent the directional sensitivity of the different cell types. The derived models are simple to apply and only require the TMS-induced electric field in the brain as input variable. The models and code are available to the general public in open-source repositories for integration into TMS studies to estimate the expected stimulation thresholds for an improved dosing and treatment planning in the future.

Use of Liquid Culture with the ElecTIS Bioreactor for Faster Recovery of Blackberry (Rubus fruticosus L.) Shoots from Conservation at 4 °C

ElecTIS is a new single container bioreactor which does not require forced air blowing, instead making the culture material mobile and the liquid medium stationary. The timed up-and-down movement of the basket containing the shoot culture ensures periodic contact with the liquid medium positioned at the base of the container. In this study we tested for the first time its use in the recovery of blackberry shoot cultures (Rubus fruticosus L., cvs Thornfree and Chester), coming from 5 months of slow growth storage (SGS), at 4 °C and in the dark. The shoot recovery at standard culture conditions was performed on two different types of ElecTIS, i.e., one with a smaller basket (ElecTISS, 234 cm2 of culture area), and one with a large basket (ElecTISL, 336 cm2), comparing the culture in TIS (cycle of 8 min every 6 h, equal to 32 min/day) with the traditional one in a gelled medium in glass jars (500 cc). After each one of the three 4-week subcultures, the shoot growth parameters and the relative growth rate highlighted a clear superiority of ElecTIS in promoting the recovery of shoot cultures coming from SGS. The analyses of chlorophyll content and stoma functionality confirmed the superior quality of shoots cultured in the ElecTIS bioreactor, and these shoots were afterwards easily rooted and acclimatized ex vitro.

Innovative curriculum design and evaluation for achieving diversity, equity and inclusion in the Indian higher education system

PurposeIndia has been withstanding increasing pressure of enrolment in the higher education system, resulting in the creation of new universities in consonance with the recommendations of the Knowledge Commission (2007). Barring a few institutions of paramount excellence, the mushrooming universities fail to conform to equitability of quality and standards, that is teaching-learning-dissemination and research, except for accommodating higher gross enrolment ratio. It has resulted in an asymmetric and sporadic development of human resources, leaving a large basket of learners out of the pursuit for aspiring higher academic, research and professional enrichment. The country needs to develop an innovative common minimum curriculum and evaluation framework, keeping in view the trinity of diversity, equity and inclusion (DEI) across the Indian higher education system to deliver human resources with equitable knowledge, skill and intellectual acumen.Design/methodology/approachThe paper has been developed using secondary information.FindingsThe manuscript has developed an innovative teaching-learning framework that would ensure every Indian HEI to follow a common minimum curriculum and partial common national evaluation system so that the learners across the country would enjoy the essence of equivalence.Originality/valueThis research has designed a comprehensive model to integrate the spirit of the “DEI” value proposition in developing curriculum and gearing common evaluation. This would enable the country to reinforce the spirit of social equity and the capacity to utilise resources with equitability and perpetuity.

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells.

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory. Computer models are widespread in neuroscience, where they are used to mimic brain function at different levels. These models offer a variety of new possibilities for the neuroscientist, but also numerous challenges, such as: where to sample the input space for the simulator, how to make sense of the data that is generated, and how to estimate unknown parameters in the model. Statistical emulation can be a valuable complement to simulator-based research. Emulators are able to mimic the simulator, often with a much smaller computational burden and they are especially valuable for parameter estimation, which may require many simulator evaluations. This work compares different statistical models that address these challenges, and applies them to simulations of neocortical L2/3 large basket cells, created and run with the NEURON simulator in the context of the European Human Brain Project. The novelty of our approach is the use of fast empirical emulators, which have the ability to accelerate the optimization process for the simulator and to identify which inputs (in this case, different membrane ion channels) are most influential in affecting simulated features. These contributions are complementary, as knowledge of the important features can further improve the optimization process. Subsequent research, conducted after the process is completed, will gain efficiency by focusing on these inputs.

Contatti linguistici lungo le coste tirreniche: storia della parola marruffo

Abstract The article intends to reconstruct the linguistic history of a particular fishing gear called marruffo, which is still used in the Gulf of Naples and in a few places of the North Tyrrhenian coasts. The marruffo is a fishing trap used by fishermen to preserve the catch while awaiting sale. Conical in shape, it looks like a large basket with a lid, in which fish or crustaceans of various types are placed. Starting from the 1871 work by the naturalist Achille Costa, entitled La pesca nel golfo di Napoli, the attestations of marruffo in Campania, Sardinia and Corsica are outlined. I put forward the hypothesis that the object arrived on the Tyrrhenian coasts as a consequence of migrations of fishermen from the Neapolitan area to the islands of Tuscany, Sardinia and Corsica between the 18th and 19th century. Since in southern Italy the name marruffo also indicates a jug for wine or water, I hypothesize that the word was extended from the lexicon of everyday life to the fishing lexicon throughout a process of resemantization, as it was demonstrated for other similar cases.

Effects of transcranial alternating current stimulation on spiking activity in computational models of single neocortical neurons

Neural oscillations are a key mechanism for information transfer in brain circuits. Rhythmic fluctuations of local field potentials control spike timing through cyclic membrane de- and hyperpolarization. Transcranial alternating current stimulation (tACS) is a non-invasive neuromodulation method which can directly interact with brain oscillatory activity by imposing an oscillating electric field on neurons. Despite its increasing use, the basic mechanisms of tACS are still not fully understood. Here, we investigate in a computational study the effects of tACS on morphologically realistic neurons with ongoing spiking activity. We characterize the membrane polarization as a function of electric field strength and subsequent effects on spiking activity in a set of 25 neurons from different neocortical layers. We find that tACS does not affect the firing rate of investigated neurons for electric field strengths applicable to human studies. However, we find that the applied electric fields entrain the spiking activity of large pyramidal neurons and large basket neurons at < 1 mV/mm field strengths. Our model results are in line with recent experimental studies and can provide a mechanistic framework to understand the effects of oscillating electric fields on single neuron activity. They highlight the importance of neuron morphology and biophysics in responsiveness to electrical stimulation.

Is inferior olive central to the pathophysiology of essential tremor? No.

Essential tremor (ET) represents one of the commonest movement disorder worldwide and is the most common tremor disorder. ET manifests with various combinations of motor and nonmotor symptoms. The clinical hallmark is a kinetic tremor of upper limbs. Historically, the pathogenesis of ET has been based on the hypothesis of an overactivity of the inferior olive (inferior olive hypothesis: IOH) where the inferior olive would act as the central pace-maker of ET, resulting in impaired electrophysiological discharges of the olivo-cerebellar tract. The absence of structural alterations in post-mortem studies of the inferior olive is a striking argument against the IOH. Furthermore, neuroimaging studies point towards the implication of the cerebello-thalamo-cerebral pathway rather than the IO, and the harmaline model which has been considered as an animal model of ET presents important weaknesses. By contrast, a series of experiments by Louis et al. have provided convincing evidence of impaired wiring of the Purkinje cell microcircuitry and progressive neurodegeneration of the cerebellar cortex. The Purkinje neuron appears as the primary culprit (Purkinjopathy). The cerebellar cortex hypothesis (CCH) has solid neuropathological signatures, unlike the purely physiological IOH. Rather than a dysregulatory electrophysiological disorder suggested by IOH, ET is a clinical-pathological entity similar to late onset neurodegenerative disorders such as Parkinson's disease or Alzheimer's disease. The CCH emphasizes the need to develop novel therapeutic strategies in order to maintain or promote the cerebellar reserve. The modern reconceptualization of ET in a genuine cerebellar disorder is cleaning the IOH to the light of histopathological studies. ET falls in the large basket of the neurodegenerative diseases and we have entered into a novel formulation of the disease pathogenesis with direct impacts on future therapies.

Using the Special Drawing Right in the Frankel-Wei regression framework

The Frankel-Wei regression framework measures the comovements between currencies, and assumes that all foreign exchange rates share a common numéraire. The International Monetary Fund's (IMF) Special Drawing Right (SDR) is a regular choice for the common numéraire. However, the five-currency basket of the SDR lacks diversification, which results in significant positive comovements between the basket currencies and the SDR currency basket. Consequently, the estimator of the regression coefficient is biased away from its true value. We suggest that the common numéraire be a large well-diversified currency basket, rather than a small undiversified currency basket, such as the five-currency SDR.

Pricing the correlation skew with normal mean-variance mixture copulas

In this paper we propose a new pricing methodology for European multi-asset options based on the family of normal mean-variance mixture copulas. The goal is to develop a copula-based method with the flexibility to reproduce the correlation skew, and at the same time efficient enough to be used for large baskets. Simplicity and ease of implementation are also properties of the model. After presenting the relevant pricing formulae, the methodology is applied to several market problems where the correlation skew is involved in different ways.

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.

Fundamental basket size patterns and their relation to retailer performance

This study uses a sample of approximately 60,000 US households to document fundamental shopping basket size patterns across a range of retail types, and examines them in relation to retailer performance metrics (unit sales and dollar revenue). Specifically, this research addresses two main questions: 1) how do shopping basket metrics (mean and median number of items, the distribution of one, two, three … n items) differ by retail type, and 2) how does the Pareto ratio (sales generated by the heaviest 20%, and lightest 80% of buyers) apply to shopping baskets. The results show that basket size patterns in retailers are predictable. Shoppers purchase more items on average in retailers that offer a greater variety of items, and the distribution of basket sizes follows the Poisson lognormal model. The results also show that the largest 20% of shopping baskets on average generate 50% of unit sales, and 40% of dollar revenue. These results set additional benchmarks of the patterns that can be expected when looking at data on a basket-level. This research offers implications to practitioners by showing the importance of small and large baskets for retailer revenue and growth, which can guide more informed decision making to better manage their stores and brands.

PEMANFAATAN ROTAN DAN BAMBU OLEH MASYARAKAT DESA PARIT RAJA KECAMATAN SEJANGKUNG KABUPATEN SAMBAS

Forests have the potential to meet a variety of human needs such as food, medicine, timber, and handicraft. Non-timber forest product used by the community of Parit Raja Village are rattan and bamboo. This research aim to inventory of the types of rattan and bamboo and to inventory the forms of utilization of rattan and bamboo processing in Parit Raja Village of Sejangkung Sub-District of Sambas Regency. This study used a survey method with in-depth interviews with the community in Parit Raja Village. The results showed that there were 5 types of rattan and 3 types of bamboo that were utilized by people of Parit Raja Village, namely Seuti Rattan (Calamus ornatus), Marau Rattan (Korthalsia rigida), Sega Rattan (Calamus caesius), Babuai Rattan (Plectocomia elongate), Nanga Rattan (Korthalsia Junghuhnii) and Bambo, namely Abe Bamboo (Gigantochloa Balui), Kuayan Bamboo, Ater Bamboo (Gigantochloa atter). The forms of utilization of rattan by Parit Raja Village community are the furniture, living room decoration and wicker found in the Sejangkung Hamlet. The most common type of rattan used were Seuti (99.9%), while bamboo utilization ranged from furniture, wicker and cooking as found in Gambir Hamlet, Kawakan Hamlet, Sembuai Hamlet, and Rambayan Hamlet. The most commonly used bamboo species is Abe bamboo (93,3%). There are 22 handicraft product produced by the people of Parit Raja Village including sofa sets, baby swing baskets, room dividers, corner shelves, flower vases (cage model), and parcels. The forms of utilization of bamboo by the community of Parit Raja Village: there are 14 handicraft products including nyiru, capil/tanggoi, rice dishes, small rice basket, bakak ( large rice basket), and fruit basket. Keywords: Rattan, Bamboo, Parit Raja Village, Handicrafts.

The Environmental Impact of the Advent of Online Grocery Retailing

This study assesses the environmental impact of the advent of online grocery retailing. We model the grocery supply chain before and after the emergence of online grocery retail. The models include suppliers, offline and online retailers, the delivery infrastructure, and households. All firms and households optimally manage their inventory; online retailers also optimally manage deliveries. We compare food waste and transportation emissions before and after the advent of online grocery retail. We isolate three key factors that drive the difference: (i) which households switch to online shopping, (ii) their shopping patterns, and (iii) how the first two factors change where inventories are held. In general, moderate online grocery prices and delivery fees lead to (desirable) adoption primarily by households located “far” from offline stores, neither too frequent shopping nor too large basket sizes by these online households, and enough beneficial inventory centralization—and a consequent reduction in emissions. Numerical calibration using industry and demographic data reveals that in most US cities the advent of online grocery should be beneficial, leading to an eventual 8-41% reduction in emissions; more congested, wealthier, lower offline-store-density cities have the most substantial gains. Finally, making online deliveries from existing offline stores further enhances environmental benefits.

Precision medicine for locally advanced breast cancer: frontiers and challenges in Latin America.

Advances in high-throughput technologies and their involvement in the ‘omics’ of cancer have made possible the identification of hundreds of biomarkers and the development of predictive and prognostic platforms that model the management of cancer from evidence-based medicine to precision medicine. Latin America (LATAM) is a region characterised by fragmented healthcare, high rates of poverty and disparities to access to a basic standard of care not only for cancer but also for other complex diseases. Patients from the public setting cannot afford targeted therapy, the facilities offering genomic platforms are scarce and the use of high-precision radiotherapy is limited to few facilities. Despite the fact that LATAM oncologists are well-trained in the use of genomic platforms and constantly participate in genomic projects, a medical practice based in precision oncology is a great challenge and frequently limited to private practice. In breast cancer, we are waiting for the results of large basket trials to incorporate the detection of actionable mutations to select targeted treatments, in a similar way to the management of lung cancer. On the other hand and paradoxically, in the ‘one fit is not for all’ era, clinical and genomic studies continue grouping our patients under the single label ‘Latin American’ or ‘Hispanic’ despite the different ancestries and genomic backgrounds seen in the region. More regional cancer genomic initiatives and public availability of this data are needed in order to develop more precise oncology in locally advanced breast cancer.

Supply chain management: A way forward to curtail post-harvest losses and enhance farmers ’income

India over the years witnessed a marked increase in production of perishable high nutrition products like fruits and vegetables but development of cold-chain infrastructure was not strategically directed, for safe handling and to transport these perishable products to markets. A resultant demand supply mismatch emerged across these commodities, contributing to wide spread price fluctuations and inflation. Cold-chain development efforts were earlier focused on building storage capacity for single commodity bulk storages, at production end, eg. potato and dried chilies whereas the larger basket of perishable horticulture requires other infrastructure components to avail of cold-chain as a market linked intervention. It is apparent that post-harvest losses can be reduced through efficient supply chain system from the point of harvest to the point of consumption. even if the country is able to reduce 50% of the losses/wastage from the current levels, the farmer's income will be sustainably enhanced and many rural employment opportunities will be created. In tomato supply chain study, it is concluded that improved practices have been widely adopted on the farm (improved varieties, trellising, marigolds as trap plants), best practices during harvesting (use of maturity indices, careful handling and picking aids), field handling (use of shade) and during the postharvest period (use of plastic crates, shade for sorting/grading practices) can lead to post harvest loss reduction by 10 percentage points and can cater to Vitamin C requirement of 1.6 billion people per year.

Towards a supervised classification of neocortical interneuron morphologies

BackgroundThe challenge of classifying cortical interneurons is yet to be solved. Data-driven classification into established morphological types may provide insight and practical value.ResultsWe trained models using 217 high-quality morphologies of rat somatosensory neocortex interneurons reconstructed by a single laboratory and pre-classified into eight types. We quantified 103 axonal and dendritic morphometrics, including novel ones that capture features such as arbor orientation, extent in layer one, and dendritic polarity. We trained a one-versus-rest classifier for each type, combining well-known supervised classification algorithms with feature selection and over- and under-sampling. We accurately classified the nest basket, Martinotti, and basket cell types with the Martinotti model outperforming 39 out of 42 leading neuroscientists. We had moderate accuracy for the double bouquet, small and large basket types, and limited accuracy for the chandelier and bitufted types. We characterized the types with interpretable models or with up to ten morphometrics.ConclusionExcept for large basket, 50 high-quality reconstructions sufficed to learn an accurate model of a type. Improving these models may require quantifying complex arborization patterns and finding correlates of bouton-related features. Our study brings attention to practical aspects important for neuron classification and is readily reproducible, with all code and data available online.

The Economics of Saltfish Production in the Aegean During the Classical and Hellenistic Periods

Despite a dearth of literary and archaeological evidence for the commercial production of salted fish or fish sauces in the Aegean during the Classical and Hellenistic periods it has been argued, based on a variety of proximate data, that such production must have been common. This paper suggests those arguments are probably wrong. It argues first that the absence of archaeological evidence for regional Aegean production and trade is itself not necessarily meaningful since a similar absence exists for the Black Sea region during the Classical and Hellenistic periods when commercial production and trade is otherwise well attested; in the Black Sea the most common varieties of saltfish were produced without the use of permanent installations such as salting vats and shipped not in amphoras but in large baskets, thereby leaving little trace in the archaeological record. Evidence for regional Aegean production is also, however, largely absent from the literary and epigraphic sources where a number of key pieces of evidence have been misinterpreted. The evidence suggests instead that commercial catches even of species well suited for preservation would have been marketed fresh. This can be explained in part by the fact that in the Aegean different environmental constraints obtained. More importantly, institutional factors often would have made the commercial production and trade of salted fish and fish sauces uneconomical. Even where local conditions of glut periodically prevailed the possibility of household production may have prevented the development of commercial production on any meaningful scale.

Machine Learning for Algorithmic Trading and Trade Schedule Optimization

In this paper we present a machine learning technique that can be used in conjunction with multi-period trade schedule optimization used in program trading. The technique is based on an artificial neural network (ANN) model that determines a better starting solution for the non-linear optimization routine. This technique provides calculation time improvements that are 30% faster for small baskets (n = 10 stocks), 50% faster for baskets of (n = 100 stocks) and up to 70% faster for large baskets (n ≥ 300 stocks). Unlike many of the industry approaches that use heuristics and numerical approximation, our machine learning approach solves for the exact problem and provides a dramatic improvement in calculation time.