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We study the nonparametric identification of gross output production functions under the environment of the commonly employed proxy variable methods. We show that applying these methods to gross ou...

In this paper we have performed drug classification using machine learning models like random forest, decision tree, and logistic regression. To further understand how these models came to their conclusion, we find the interpretability of these models using LIME and SHAP. Towards the end, we found that LIME and SHAP can be used to gain insights into a Machine Learning model and conclude which feature is responsible for the deviation of the results. According to the LIME and SHAP results, Random Forest and Decision Tree ML models are the most suited models for drug classification as both achieved an accuracy of 0.975. Also, Na to K and BP were found to be the most essential features in predicting the outcome.

This is an invited chapter for the forthcoming Volume 4 of the Handbook of Industrial Organization. We present empirical models of demand and supply in differentiated products industries with an emphasis on the key ideas arising from the recent applied literature. We start with a discussion of the challenges in modeling and estimation of demand for differentiated products, and focus on discrete choice characteristics-based demand models that address these challenges while allowing enough flexibility to capture realistic substitution patterns. Our discussion emphasizes how empirical strategies can leverage different features of data depending on the sources of variation that are commonly found in applied work. Moving to the supply-side, we show how demand estimates combined with a pricing model, can be used to recover markups and marginal costs. We also show how the model of pricing can be tested. We discuss a baseline Bertrand-Nash model of competitive pricing, and expand it to cover a) coordinated pricing, b) wholesale relationships, and c) bargaining. We end the chapter with extensions of the demand model, including dynamic and continuous demand.

Introduction. This in-vitro study aims to evaluate the effect of acidic environment and intracanal medicament on push out bond strength of Biodentine and Mineral Trioxide Aggregate Plus (MTA Plus) Method. Forty extracted single rooted teeth were sectioned below the cement-enamel junction. The root canals were instrumented using rotary files and then peeso reamer was used to obtain standardized root canal dimension. Specimens were randomly classified into following groups- Group 1: calcium hydroxide in the absence of acidic environment; Group 2: calcium hydroxide in the presence of acidic environment; Group 3: no intracanal medicament in the absence of acidic environment; Group 4: no intracanal medicament in the presence of acidic environment. Specimens were kept for 7 days at room temperature. Thereafter, specimens of each group were transversely sectioned into 1 mm thick slices and divided into 2 sub-groups according to the use of biodentine and MTA Plus. Using Universal Testing Machine, push out bond strength test was carried out and the data were analyzed statistically. Results. There was no statistically significant difference in the bond strength of biodentine and MTA Plus (P>0.05). For both MTA Plus and biodentine, with or without calcium hydroxide, the push out bond strength was less in acidic environment and this difference was more pronounced without calcium hydroxide. In all the four groups, MTA plus showed comparable bond strength to biodentine. Conclusion. MTA Plus is a viable option for apexification. The push out bond strength of Biodentine and MTA Plus is impaired by acidic environment. Prior application of calcium hydroxide slightly increased the bond strength, though the difference was statistically insignificant.

5525 Background: Improved long-term results can be achieved in advanced epithelial ovarian cancer (EOC) patients using optimal cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC). Methods: Indian society of peritoneal surface malignancy (ISPSM) is a registered body which maintains prospective data of 26 centers across India who perform CRS –HIPEC. From February 2017 until January 2022, 1470 patients with advanced EOC were treated with CRS-HIPEC. He general practice patterns and the oncological outcomes in terms of progression free survival (PFS) and overall survival (OS) & post-operative morbidity and mortality is reported. Results: Upfront (n = 156), interval (n = 645) and recurrent (n = 669) cytoreductions were performed based on the timeline at presentation. Mean age 54.5±10.74, PCI 13. 6±5.2, duration of surgery 10.6±1.h hrs. 36.4% had total peritonectomy, 12.7% had multivisceral resection, 41.8%had bowel resections and stoma rate was 7.4%. 60.3% had semiopen HIPEC, 83.1% used cisplatin for HIPEC and 83.1 % had HIPEC for 90 minutes. Overall G3-G5 morbidity was 25.4% with major ones being post-operative intra-abdominal collection (21.8%), electrolyte imbalance (16.4%), pulmonary (16.4%) followed by hematological (12.7%). Surgical morbidity was more in upfront cytoreduction group compared to interval group (20% versus 13.5%) and recurrent group (20% versus 15%), respectively. The 30 day mortality was 3.8%. With a median follow-up of 46 months, median PFS was 33 months in primary (upfront plus interval) group and 16 months in recurrent cytoreduction group. Median OS was not achieved in both primary and recurrent groups (4 year OS rates: 60 and 55%, respectively). Conclusions: This prospective database provides a collation and audit of the management of advanced epithelial ovarian cancer with CRS HIPEC in multiple centers registered under ISPSM. In advanced EOC patients, CRS plus HIPEC offers potential benefits in PFS and OS rates, with acceptable rates of morbidity and mortality and can be practiced even in resource constrained setting.

Instrumental variables (IVs) are a commonly used technique for causal inference from observational data. However, in the recent years, the use of the IV method has come under much criticism across multiple disciplines (e.g. [1] and [6] in Economics; [3] in Marketing; [5], [4], and [2] in Finance). This is because, in practice, the variation induced by IVs can be limited, which yields imprecise or biased estimates of causal effects and renders the approach ineffective for policy decisions. In this paper, we confront these challenges by formulating the problem of constructing instrumental variables from candidate exogenous information as a (supervised) machine learning problem that is amenable to the learning approach. We extend the standard learning framework to develop an algorithm we term MLIV (machine-learned instrumental variables), which allows training of instruments and causal inference to be simultaneously performed from sample data. We provide formal asymptotic theory and show O(√n) consistency and asymptotic normality for machine-learned instrument variables. We illustrate the effectiveness of the MLIVs in empirical environments consisting of both linear and nonlinear model parameters. Simulations and application to real-world data demonstrate that the algorithm is highly effective and significantly improves the performance of causal inference from observational data. The complete version of this paper can be found at https://ssrn.com/abstract=3352957.

FcRn and CD32a form a ternary complex under acidic conditions and act together in determining responses to IgG immune complexes. The human autoimmune disease–associated CD32a-H131 variant more avidly forms this ternary complex, leading to greater FcRn-dependent immune responses to IgG., IgG immune complexes (ICs) promote autoimmunity through binding fragment crystallizable (Fc) γ-receptors (FcγRs). Of these, the highly prevalent FcγRIIa (CD32a) histidine (H)-131 variant (CD32aH) is strongly linked to human autoimmune diseases through unclear mechanisms. We show that, relative to the CD32a arginine (R)-131 (CD32aR) variant, CD32aH more avidly bound human (h) IgG1 IC and formed a ternary complex with the neonatal Fc receptor (FcRn) under acidic conditions. In primary human and mouse cells, both CD32a variants required FcRn to induce innate and adaptive immune responses to hIgG1 ICs, which were augmented in the setting of CD32aH. Conversely, FcRn induced responses to IgG IC independently of classical FcγR, but optimal responses required FcRn and FcγR. Finally, FcRn blockade decreased inflammation in a rheumatoid arthritis model without reducing circulating autoantibody levels, providing support for FcRn’s direct role in IgG IC-associated inflammation. Thus, CD32a and FcRn coregulate IgG IC-mediated immunity in a manner favoring the CD32aH variant, providing a novel mechanism for its disease association.

Dens invaginatus (DI) as a dental anomaly suggests a broad spectrum of morphologic variations and predisposes the tooth to decay and in intense invaginations to pulpitis and apical periodontitis. The involved tooth requires endodontic or combined endodontic-surgical treatment which often is complicated because of the abnormal morphology. As intraoral periapical radiographs provide insufficient information because of its two-dimensional nature, a cone-beam computed tomographic scan is recommended in complex cases with aberrant root canal anatomy that allows visualization of pathology in three dimensions. This article reports a case in which multiple teeth were involved with DI associated with open apex and periapical pathology which was successfully treated with endodontic and combined endodontic-surgical approach. The success of the present case suggest MTA as a preferable material to aid regeneration of the apical tissue in nonvital teeth with open apex and thus can be used in cases of DI.

Endoplasmic reticulum aminopeptidase 1 (ERAP1) is involved in the final processing of peptide precursors to generate the N-termini of MHC class I-restricted epitopes. ERAP1 thus influences immunodominance and cytotoxic immune responses by controlling the peptide repertoire available for cell surface presentation by MHC molecules. To enable this critical role in antigen processing, ERAP1 trims peptides by a unique molecular ruler mechanism that turns on/off hydrolysis activity in a peptide-length and -sequence dependent manner. Thus unlike other aminopeptidases, ERAP1 could recognize both the N- and C-termini of peptides in order to read the substrate's length. To exemplify and validate this molecular ruler mechanism, we have carried out crystallographic studies on molecular recognition of antigenic peptide's C-terminus by ERAP1. In this report, we have determined a 2.8Å-resolution crystal structure of an intermolecular complex between the ERAP1 regulatory domain and a natural epitope's C-terminus displayed in a fusion protein. It reveals the structural details of peptide's C-termini recognition by ERAP1. ERAP1 uses specificity pockets on the regulatory domain to bind the peptide's carboxyl end and side chain of the C-terminal anchoring residue. At the same time, flexibility in length and sequence at the middle of peptides is accommodated by a kink with minimal interactions with ERAP1.

We study the estimation of substitution patterns within the discrete choice framework developed by Berry (1994) and Berry, Levinsohn, and Pakes (1995). Our objective is to demonstrate the consequences of using weak instruments in this non-linear GMM context, and propose a new class of instruments that are designed to avoid weak IV and can be used to estimate a large family of models with aggregate data. We argue that strong instruments should reflect the (exogenous) degree of differentiation of each product in a market (Differentiation IVs), and provide a series of examples to illustrate the performance of simple instrument functions.

We show that even in the absence of data on individual decisions, the distribution of individual attitudes towards risk can be identified from the aggregate conditions that characterize equilibrium on markets for risky assets. Taking parimutuel horse races as a textbook model of contingent markets, we allow for heterogeneous bettors with very general risk preferences, including non-expected utility. Under a standard single-crossing condition on preferences, we identify the distribution of preferences among the population of bettors and we derive testable implications. We estimate the model on data from U.S. races. Specifications based on expected utility fit the data very poorly. Our results stress the crucial importance of nonlinear probability weighting. They also suggest that several dimensions of heterogeneity may be at work.

In this paper we introduce a new approach to estimating differentiated product demand systems that allows for products with zero sales in the data. Zeroes in demand are a common problem in product differentiated markets, but fall outside the scope of existing demand estimation techniques. Our solution to the zeroes problem is based on constructing bounds for the conditional expectation of the inverse demand. These bounds can be translated into moment inequalities that are shown to yield consistent and asymptotically normal point estimator for demand parameters under natural conditions for differentiated product markets. In Monte Carlo simulations, we demonstrate that the new approach works well even when the fraction of zeroes is as high as 95%. We apply our estimator to supermarket scanner data and find that correcting the bias caused by zeroes has important empirical implications, e.g., price elasticities become on the order of twice as large when zeroes are properly controlled.

Therapeutic blockade of FcRn in humans decreases IgG and IgG immune complex levels with the attendant immunologic implications., The neonatal crystallizable fragment receptor (FcRn) functions as an intracellular protection receptor for immunoglobulin G (IgG). Recently, several clinical studies have reported the lowering of circulating monomeric IgG levels through FcRn blockade for the potential treatment of autoimmune diseases. Many autoimmune diseases, however, are derived from the effects of IgG immune complexes (ICs). We generated, characterized, and assessed the effects of SYNT001, a FcRn-blocking monoclonal antibody, in mice, nonhuman primates (NHPs), and humans. SYNT001 decreased all IgG subtypes and IgG ICs in the circulation of humans, as we show in a first-in-human phase 1, single ascending dose study. In addition, IgG IC induction of inflammatory pathways was dependent on FcRn and inhibited by SYNT001. These studies expand the role of FcRn in humans by showing that it controls not only IgG protection from catabolism but also inflammatory pathways associated with IgG ICs involved in a variety of autoimmune diseases.

We show standard methods to estimate production functions do not identify markups. This nonidentification creates spurious skewness in estimated markup distributions. We also show that ex-ante structure on the returns to scale solves the identification problem. In US public firm data and in a Monte Carlo experiment, we find that applying constant returns to scale performs remarkably well and reduces the skewness in the markup distribution among public-firm by as much as half in comparison to nonidentified estimates. This results in half the efficiency losses in output and labor shares when calibrated to a recent macroeconomic model.

Instrumental variables (IVs) are a commonly used technique for causal inference from observational data. In practice, the variation induced by IVs can be limited, which yields imprecise or biased estimates of causal effects and renders the approach ineffective for policy decisions. We confront this challenge by formulating the problem of constructing instrumental variables from candidate exogenous data as a machine learning problem. We propose a novel algorithm, called MLIV (machine-learned instrumental variables), which allows learning of instruments and causal inference to be simultaneously performed from sample data. We provide formal asymptotic theory and show root-n consistency and asymptotic efficiency of our estimators hold under very general conditions. Simulations and application to real-world data demonstrate that the algorithm is highly effective and significantly improves the performance of causal inference from observational data.

Testable predictions of many economic models involve inequality comparisons between transformations of nonparametric functionals. We introduce an econometric test for these types of restrictions based on one-sided L p -statistics that adapt asymptotically to the contact sets without having to directly estimate them. Monte Carlo experiments show that our test is less conservative than procedures based on least-favorable configurations and has power comparable to other contact-set based procedures. As an application, we test for interdependence of bidders’ valuations in ascending auctions. Using USFS timber auction data we reject the Independent Private Values model in favor of a model of correlated private values.

We show how to nonparametrically identify the distribution of unobservables, such as random coefficients, that characterizes the heterogeneity among consumers in multinomial choice models. We provide general identification conditions for a class of nonlinear models and then verify these conditions using the primitives of the multinomial choice model. We require that the distribution of unobservables lie in the class of all distributions with finite support, which under our most general assumptions, resembles a product space where some of the product members are function spaces. We show how identification leads to the consistency of a nonparametric estimator.

T-cell immunoglobulin and mucin domain containing protein-3 (TIM-3) is an important immune regulator. Here, we describe a novel high resolution (1.7 Å) crystal structure of the human (h)TIM-3 N-terminal variable immunoglobulin (IgV) domain with bound calcium (Ca++) that was confirmed by nuclear magnetic resonance (NMR) spectroscopy. Significant conformational differences were observed in the B-C, C′-C″ and C′-D loops of hTIM-3 compared to mouse (m)TIM-3, hTIM-1 and hTIM-4. Further, the conformation of the C-C′ loop of hTIM-3 was notably different from hTIM-4. Consistent with the known metal ion-dependent binding of phosphatidylserine (PtdSer) to mTIM-3 and mTIM-4, the NMR spectral analysis and crystal structure of Ca++-bound hTIM-3 revealed that residues in the hTIM-3 F-G loop coordinate binding to Ca++. In addition, we established a novel biochemical assay to define hTIM-3 functionality as determined by binding to human carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1). These studies provide new insights useful for understanding and targeting hTIM-3.

This paper studies belief heterogeneity in a benchmark competitive asset market: a market for Arrow-Debreu securities. We show that dierences in agents’ beliefs lead to a systematic pricing pattern, the favorite longshot bias (FLB): securities with a low payout probability are overpriced while securities with high probability payout are underpriced. We apply demand estimation techniques to betting market data, and find that the observed FLB is explained by a two-type population consisting of canonical traders, who hold virtually correct beliefs and are the majority type in the population (70%); and noise traders exhibiting significant belief dispersion. Furthermore, using formal model comparisons and also exploiting variation in public information across markets in our dataset, we show that our belief heterogeneity model empirically outperforms existing preference-based explanations of the FLB, such as risk-loving or prospect theory.

ASD one of the most common acyanotic congenital heart disease in women of child bearing age and pregnancy, it accounts for about 10% of all congenital heart disease. During pregnancy ASD is usually well tolerated. Bronchial asthma can complicate 1-7% of pregnancies. Uncontrolled asthma may produce serious maternal and fetal complications like PAH, fetal hypoxemia. These patients are considered to have high risk for anaesthesia due to increased perioperative cardiovascular and pulmonary complications. During anaesthesia our objectives are to avoid hypotension, hypoxemia, reversal of shunt and fluid overload.

The neonatal crystallizable fragment receptor (FcRn) is responsible for maintaining the long half-life and high levels of the two most abundant circulating proteins, albumin and IgG. In the latter case, the protective mechanism derives from FcRn binding to IgG in the weakly acidic environment contained within endosomes of hematopoietic and parenchymal cells, whereupon IgG is diverted from degradation in lysosomes and is recycled. The cellular location and mechanism by which FcRn protects albumin are partially understood. Here we demonstrate that mice with global or liver-specific FcRn deletion exhibit hypoalbuminemia, albumin loss into the bile, and increased albumin levels in the hepatocyte. In vitro models with polarized cells illustrate that FcRn mediates basal recycling and bidirectional transcytosis of albumin and uniquely determines the physiologic release of newly synthesized albumin into the basal milieu. These properties allow hepatic FcRn to mediate albumin delivery and maintenance in the circulation, but they also enhance sensitivity to the albumin-bound hepatotoxin, acetaminophen (APAP). As such, global or liver-specific deletion of FcRn results in resistance to APAP-induced liver injury through increased albumin loss into the bile and increased intracellular albumin scavenging of reactive oxygen species. Further, protection from injury is achieved by pharmacologic blockade of FcRn–albumin interactions with monoclonal antibodies or peptide mimetics, which cause hypoalbuminemia, biliary loss of albumin, and increased intracellular accumulation of albumin in the hepatocyte. Together, these studies demonstrate that the main function of hepatic FcRn is to direct albumin into the circulation, thereby also increasing hepatocyte sensitivity to toxicity.

The type I membrane protein receptor carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) distinctively exhibits significant alternative splicing that allows for tunable functions upon homophilic binding. CEACAM1 is highly expressed in the tumor environment and is strictly regulated on lymphocytes such that its expression is restricted to activated cells where it is now recognized to function in tolerance pathways. CEACAM1 is also an important target for microbes which have co-opted these attributes of CEACAM1 for the purposes of invading the host and evading the immune system. These properties, among others, have focused attention on CEACAM1 as a unique target for immunotherapy in autoimmunity and cancer. This review examines recent structural information derived from the characterization of CEACAM1:CEACAM1 interactions and heterophilic modes of binding especially to microbes and how this relates to CEACAM1 function. Through this, we aim to provide insights into targeting CEACAM1 for therapeutic intervention.

We introduce and apply a new nonparametric approach to identification and inference on data from ascending auctions. We exploit variation in the number of bidders across auctions to nonparametrically identify useful bounds on seller profit and bidder surplus using a general model of correlated private values that nests the standard independent private values (IPV) model. We also translate our identified bounds into closed form and asymptotically valid confidence intervals for several economic measures of interest. Applying our methods to much studied U.S. Forest Service timber auctions, we find evidence of correlation among values after controlling for a rich vector of relevant auction covariates; this correlation causes expected profit, the profit-maximizing reserve price, and bidder surplus to be substantially lower than conventional (IPV) analysis of the data would suggest.

Introduction and objective: The aim of the present study was to compare root canal preparation with rotary ProTaper files and hand ProTaper files to find a better instrumentation technique for maintaining root canal geometry with the aid of computed tomography. Material and methods: Twenty curved root canals with at least 10 degree of curvature were divided into 2 groups of 10 teeth each. In group I the canals were prepared with hand ProTaper files and in group II the canals were prepared with rotary ProTaper files. Image analysis was performed at four levels 4mm, 6mm, 9mm, and 12mm from the root apex to assess changes in canal transportation and centering ratio using computed tomography (CT). Results: Data suggest that rotary ProTaper files presented the best outcomes for both variables evaluated. Rotary ProTaper files caused lesser transportation and remained better centered in the canal than hand ProTaper files. Conclusion: The canal preparation in natural teeth with rotary Protaper files showed lesser transportation and better centering ration than hand ProTaper files.

Improved Cook Stoves (ICSs) present a range of benefits such as decreased fuel consumption and improved air quality. However, in order for these benefits to be realized a household must adopt and consistently use the ICS. This paper documents the first phase of a stove adoption study conducted in Soroti, Uganda with a locally manufactured Tier 2 efficiency cookstove, tested under IWA 11. A market-based approach was used to disseminate ICSs in the local community to a group of 40 participant households. Study participants were divided into three groups non-users, new users and existing users. Initial field interviews were conducted with all participants to understand their perceptions of the stove and reported usage patterns. The most common reason cited for purchasing the stove by new users was fuel savings. Additionally, 130 days of usage was collected using a custom made Stove Use Monitor (SUM). The SUMs indicate that existing users consistently use the ICS. New users exhibit low and inconsistent usage during the initial 35 days of owning the ICS, but within approximately 75 days' increase usage and follow same pattern as the existing user group.

The replacement of diesel- or grid-powered water pumps with solar energy offers environmental, economic, and social benefits via climate change mitigation, improved livelihoods, and greater quality of life. As a result, India's government is promoting solar pumping technologies via direct capital subsidies, financing schemes, and legal and regulatory development. Despite such attention, and while solar pump systems have shown significant promise, challenges in implementation continue to prevent the full realization of environmental, economic, and social gains. In this paper, we examine three small-scale system implementation models across India: grant-funded pay-it-forward systems for agricultural use in Uttar Pradesh, grid-tied irrigation systems in Karnataka, and direct-to-customer financed systems for salt farming in Gujarat. We explore the feasibility of these models through financial analysis coupled with knowledge gained from interviews with key stakeholders, including system users, manufacturers, installers, and system integrators. We find that institutional factors weigh heavily on whether systems are properly introduced, used, and maintained. Particularly, ensuring long-term project sustainability requires sound project economics, proper system sizing, and effective pre-/post-sales service. Greater understanding of the interdependency between hydrogeological context, technological specifications and financial realities among project implementers and system users will be essential in scaling up solar pump systems effectively.

Solar lanterns have been shown to be a promising technology for providing reliable lighting access in off-grid communities or areas with intermediate power, and these technologies have shown significant market uptake in communities in Uganda. In this study, we examine the usage patterns and behaviors of existing d.light S20 and Firefly Mobile solar lantern customers in peri-urban and rural Uganda using interviews and sensor-based data collection. At the start of the study, semi-structured interviews were administered to solar lantern users to establish baseline demographic information and understand the user preference model, and users were provided an instrumented solar lantern in exchange for their current solar lantern. After a 10-day usage period, a follow-up survey was administered to assess the usage of the lantern and the instrumented product was recollected. These user responses, when compared to the data collected from the instrumentation, were shown to over-report product usage with an average error of 141%.

Genome-wide association studies have identified risk loci associated with the development of inflammatory bowel disease, while epidemiological studies have emphasized that pathogenesis likely involves host interactions with environmental elements whose source and structure need to be defined. Here, we identify a class of compounds derived from dietary, microbial, and industrial sources that are characterized by the presence of a five-membered oxazole ring and induce CD1d-dependent intestinal inflammation. We observe that minimal oxazole structures modulate natural killer T cell-dependent inflammation by regulating lipid antigen presentation by CD1d on intestinal epithelial cells (IECs). CD1d-restricted production of interleukin 10 by IECs is limited through activity of the aryl hydrocarbon receptor (AhR) pathway in response to oxazole induction of tryptophan metabolites. As such, the depletion of the AhR in the intestinal epithelium abrogates oxazole-induced inflammation. In summary, we identify environmentally derived oxazoles as triggers of CD1d-dependent intestinal inflammatory responses that occur via activation of the AhR in the intestinal epithelium.

Pyridoxal kinase catalyzes the phosphorylation of pyridoxal (PL) to pyridoxal 5'-phosphate (PLP). A D235A variant shows 7-fold and 15-fold decreases in substrate affinity and activity, respectively. A D235N variant shows approximately 2-fold decrease in both PL affinity and activity. The crystal structure of D235A (2.5 A) shows bound ATP, PL and PLP, while D235N (2.3 A) shows bound ATP and sulfate. These results document the role of Asp235 in PL kinase activity. The observation that the active site of PL kinase can accommodate both ATP and PLP suggests that formation of a ternary Enz.PLP.ATP complex could occur in the wild-type enzyme, consistent with severe MgATP substrate inhibition of PL kinase in the presence of PLP.

Pyridoxal kinase catalyzes the transfer of a phosphate group from ATP to the 5' alcohol of pyridoxine, pyridoxamine, and pyridoxal. In this work, kinetic studies were conducted to examine monovalent cation dependence of human pyridoxal kinase kinetic parameters. The results show that hPLK affinity for ATP and PL is increased manyfold in the presence of K(+) when compared to Na(+); however, the maximal activity of the Na(+) form of the enzyme is more than double the activity in the presence of K(+). Other monovalent cations, Li(+), Cs(+), and Rb(+) do not show significant activity. We have determined the crystal structure of hPLK in the unliganded form, and in complex with MgATP to 2.0 and 2.2 A resolution, respectively. Overall, the two structures show similar open conformation, and likely represent the catalytically idle state. The crystal structure of the MgATP complex also reveals Mg(2+) and Na(+) acting in tandem to anchor the ATP at the active site. Interestingly, the active site of hPLK acts as a sink to bind several molecules of MPD. The features of monovalent and divalent metal cation binding, active site structure, and vitamin B6 specificity are discussed in terms of the kinetic and structural studies, and are compared with those of the sheep and Escherichia coli enzymes.

Memory latency tolerant architectures achieve high performance by supporting thousands of in-flight instructions without scaling cycle-critical processor resources. We present new load-store processing algorithms for latency tolerant architectures. We augment primary load and store queues with secondary buffers. The secondary load buffer is a set associative structure, similar to a cache. The secondary store queue, the store redo log (SRL) is a first-in first-out (FIFO) structure recording the program order of all stores completed in parallel with a miss, and has no CAM and search functions. Instead of the secondary store queue, a cache provides temporary forwarding. The SRL enforces memory ordering by ensuring memory updates occur in program order once the miss data arrives from memory. The new algorithms remove fundamental sources of power, and area inefficiency in load and store processing by eliminating the CAM and search functions in the secondary load and store buffers, and still achieve competitive performance compared to hierarchical designs

Increased integration in the form of multiple processor cores on a single die, relatively constant die sizes, shrinking power envelopes, and emerging applications create a new challenge for processor architects. How to build a processor that provides high single-thread performance and enables multiple of these to be placed on the same die for high throughput while dynamically adapting for future applications? Conventional approaches for high single-thread performance rely on large and complex cores to sustain a large instruction window for memory tolerance, making them unsuitable for multi-core chips. We present Continual Flow Pipelines (CFP) as a new non-blocking processor pipeline architecture that achieves the performance of a large instruction window without requiring cycle-critical structures such as the scheduler and register file to be large. We show that to achieve benefits of a large instruction window, inefficiencies in management of both the scheduler and register file must be addressed, and we propose a unified solution. The non-blocking property of CFP keeps key processor structures affecting cycle time and power (scheduler, register file), and die size (second level cache) small. The memory latency-tolerant CFP core allows multiple cores on a single die while outperforming current processor cores for single-thread applications.

T-cell immunoglobulin domain and mucin domain-3 (TIM-3, also known as HAVCR2) is an activation-induced inhibitory molecule involved in tolerance and shown to induce T-cell exhaustion in chronic viral infection and cancers1–5. Under some conditions, TIM-3 expression has also been shown to be stimulatory. Considering that TIM-3, like cytotoxic T lymphocyte antigen 4 (CTLA-4) and programmed death 1 (PD-1), is being targeted for cancer immunotherapy, it is important to identify the circumstances under which TIM-3 can inhibit and activate T-cell responses. Here we show that TIM-3 is co-expressed and forms a heterodimer with carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1), another well-known molecule expressed on activated T cells and involved in T-cell inhibition6–10. Biochemical, biophysical and X-ray crystallography studies show that the membrane-distal immunoglobulin-variable (IgV)-like amino-terminal domain of each is crucial to these interactions. The presence of CEACAM1 endows TIM-3 with inhibitory function. CEACAM1 facilitates the maturation and cell surface expression of TIM-3 by forming a heterodimeric interaction in cis through the highly related membrane-distal N-terminal domains of each molecule. CEACAM1 and TIM-3 also bind in trans through their N-terminal domains. Both cis and trans interactions between CEACAM1 and TIM-3 determine the tolerance-inducing function of TIM-3. In a mouse adoptive transfer colitis model, CEACAM1-deficient T cells are hyper-inflammatory with reduced cell surface expression of TIM-3 and regulatory cytokines, and this is restored by T-cell-specific CEACAM1 expression. During chronic viral infection and in a tumour environment, CEACAM1 and TIM-3 mark exhausted T cells. Co-blockade of CEACAM1 and TIM-3 leads to enhancement of anti-tumour immune responses with improved elimination of tumours in mouse colorectal cancer models. Thus, CEACAM1 serves as a heterophilic ligand for TIM-3 that is required for its ability to mediate T-cell inhibition, and this interaction has a crucial role in regulating autoimmunity and anti-tumour immunity.

In this paper we introduce a new approach to estimating a differentiated product demand system that allows for error in market shares as measures of choice probabilities. In particular, our approach allows for products with zero sales in the data, which is a frequent phenomenon that arises in product differentiated markets but lies outside the scope of existing demand estimation techniques. Although we find that error in market shares generally undermine the standard point identification of discrete choice models of demand, we exploit shape restrictions on demand implied by discrete choice to generate a system of moment inequalities that partially identify demand parameters. These moment inequalities are fully robust to the variability in market shares yet are also adaptive to the information revealed by market shares in a way that allows for informative inferences. In addition, we construct a profiling approach for parameter inference with moment inequalities, making it feasible to study models with a large number of parameters (as typically required in demand applications) by focusing attention on a profile of the parameters, such as the price coefficient. We use our approach to study consumer demand from scanner data using the Dominick's Finer Foods database, and find that even for the baseline logit model, demand elasticities nearly double when the full error in market shares is taken into account.