Animal experiments were conducted following protocols approved by

Animal experiments were conducted following protocols approved by Administrative Panel on Laboratory Animal Care at Stanford University. Mice were anesthetized

with tribromoethanol and perfused with 10 ml of PBS, followed by 50 ml of fixative (4% paraformaldehyde diluted in PBS). The brains were removed and postfixed for 3 hr at room temperature and then immersed in 30% sucrose solution overnight before being sectioned at GABA agonists list 30 μm thickness on a cryostat. The free-floating brain sections were collected in PBS and counterstained with DAPI. The brain sections were mounted onto glass slides with Vectashield mounting medium (Vector Laboratories). Micoscopic photos were taken with a Leica DM IRE2 microscope. Photos taken with 10× objective were tiled to generate the image of the whole brain sections. Cultured neurons

were homogenized in lysis buffer (1% SDS, 10 mM Tris), mixed with 6× loading buffer (0.5 M tris, 60% glycerol, 10% SDS, 10% Beta-Mercaptoethanol, and 0.01% bromphenol blue), and denatured at 100°C for 20 min. After centrifugation at 14,000 rpm for 30 min, the supernatants were loaded for SDS-PAGE and immunoblotted with standard chemiluminescence protocols. The primary antibodies used in the study include: anti-syt1 (CL41.1), anti-syb2 (CL69.1), and Synx1 (U6251). Blots were digitized and quantified with National Institutes of Health image software. All band intensities were normalized

to that of control samples. MEK inhibitor We thank Dr. Mark Kay (Stanford University) and Dr. Eric J. Nestler (Mount Sinai Medical School) for AAV vectors and AAV preparation to protocols. This work was supported by NIMH Conte Center project number 5 P50 MH086403-03. “
“The range of natural signals exceeds the dynamic range of neurons. As a result, neural circuits adapt so as to more efficiently encode the recent history of inputs. One widespread example of this process occurs in response to a change in the magnitude of fluctuations, or the variance of a sensory input (Laughlin, 1989). Variance adaptation occurs in many sensory systems, including the vertebrate retina and visual cortex, the fly visual system, and the avian auditory forebrain (Fairhall et al., 2001, Nagel and Doupe, 2006, Ohzawa et al., 1985, Shapley and Victor, 1978 and Smirnakis et al., 1997). When the stimulus environment changes from a low to high variance, temporal filtering quickly accelerates, sensitivity decreases, and the average response increases. (Baccus and Meister, 2002, Chander and Chichilnisky, 2001 and Kim and Rieke, 2001). When the environment maintains a high variance, slow changes occur over 1–10 s, comprised mostly of a homeostatic decay in the average response that opposes the fast change in baseline. (Baccus and Meister, 2002, Fairhall et al., 2001 and Nagel and Doupe, 2006). Upon a decrease in contrast, all these changes reverse direction.

To determine how well the model fit the neuronal data, average fi

To determine how well the model fit the neuronal data, average firing rates per neuron for nine stimulus conditions (plotted along the x axes in Figures 5B–5D) were fit to (3A) and (3B). Variations in the parameter β correspond to neuron-to-neuron differences in the top-down attention signal. There are two hypothetical mechanisms by which attention modulations of firing rates could become correlated with the strength of normalization of the MT neurons: (1) the top-down attention signal per sensory neuron could covary with the normalization

strength of each sensory neuron, or (2) variance in the tuned normalization mechanism alone could result in attention modulation variance across the neurons. To test the first hypothesis, we determined whether or not the top-down attention signal parameter selleck (β) is correlated with the tuned normalization parameter (α) across neurons. When β and α are fit as buy Pomalidomide free parameters in Equation 3 (along with free parameters LP, LN, and σ) the value of β is not significantly correlated with α ( Figure 5A). The attention signal (β) did not covary with the normalization strength

(normalization modulation index) of each sensory neuron (R = 0.06, p = 0.55). Therefore, in subsequent analyses

we fixed β at 2.75 (its mean when estimated as a free parameter) for all neurons (see Experimental Procedures), to determine whether variance in the tuned normalization parameter alone could result in attention modulation variance across neurons. Even with β fixed, Equation 3 provided an excellent fit of the data based on the four remaining free parameters (α, LP, LN, σ). Using this approach Equation 3 explained > 99% of the variance in the mean responses of a particularly well-fit averaging neuron (neuron 3, Figure 5B), which demonstrated Fossariinae a strong normalization (P versus P+N) and a large attention modulation (PAtt+N versus P+NAtt). Similarly, Equation 3 explained 97% of the variance in the mean responses of a particularly well-fit winner-take-all neuron (neuron 4, Figure 5C) that demonstrated minimal normalization and attention modulation. Across the entire sample of MT neurons, the average explained variance was 95% ( Figure 5D). Equation 3 not only accommodates broad ranges of normalization and modulation by attention but also accounts for the asymmetric effects of attending to the preferred versus the null stimulus in the receptive field (Figure 4).

74% ± 4 75% of stimulations in the PL The evoked SB started in t

74% ± 4.75% of stimulations in the PL. The evoked SB started in the Cg 102 ± 10 ms and in the PL 103.1 ± 7.7 ms after the onset of stimulus (Figures 7B and 7C). Similar results were obtained when repetitive stimulation at 10 or 100 Hz was used. The effect of electrical stimulation on the CA1 region might be strengthened by costimulation of the neighboring alvear pathway (Deller et al., 1996). Remarkably, the occurrence of evoked SB increased on the anterior-posterior axis (Figure S7B), confirming that the density of functional projections to the PFC increases from the dorsal

to ventral Hipp (Hoover and Vertes, 2007). These data indicate that hippocampal projections that innervate the neonatal PFC selleck kinase inhibitor are an ideal candidate for mediating the hippocampal drive to the PFC. To confirm the contribution of hippocampal drive to the generation of oscillatory rhythms in the neonatal PFC, three experimental approaches were additionally used. In the first instance, the intermediate and ventral but not dorsal Hipp were excitotoxically lesioned at P1, and the consequences on prefrontal-hippocampal networks were investigated at the end of the first postnatal week. Neonatal rats (n = 12) received a small volume (20–50 nl) of 40 mM buy Erastin NMDA (lesioned pups) or of 0.1 M PBS (sham pups) according to a previously

described protocol (Lipska et al., 1993). The features of the NMDA-induced lesion were assessed post-mortem after Nissl staining. Characteristic cavitation, tissue loss, and gliosis (Bertrand et al., 2010) were present in lesioned pups, but not in the PBS-treated pups. The lesion extent, however, differed considerably across animals (Figures 8A and 8B). The CA1 and CA3 areas of the intermediate and ventral, but not dorsal Hipp were mainly affected. In some cases (n = 2), damage extended to the neighboring EC (Figure 8A). Moreover, lesions were mostly associated with a robust enlargement of the lateral ventricles. Because

an excitotoxic lesion may generally impair the development of pups by affecting their behavior and feeding abilities, we investigated the developmental milestones of PBS- and NMDA-treated animals. Their daily weight gain and general behavior (sleep-awake either cycle, righting and grasping reflexes, feeding and locomotor behavior) were similar, indicating that the excitotoxic lesion did not impair the neonatal development. Whereas PBS treatment of the Hipp did not modify the features of prefrontal SB and NG, NMDA-induced lesion affected them. The occurrence of cingulate and prelimbic SB as well as of cingulate NG slightly decreased after hippocampal lesion, yet not at significant level. More prominent were the NMDA effects on the occurrence of prelimbic NG that decreased from 0.65 ± 0.16 bursts/min in PBS-treated pups to 0.06 ± 0.04 bursts/min (p < 0.05) (Figure 8C). The amplitude, duration, and main frequency of SB and NG did not change after NMDA lesion.

This could, in turn, inform a time-dependent model of gain contro

This could, in turn, inform a time-dependent model of gain control (e.g., Model 7 in Table S2), though we did not cross-validate such a model. Reliable estimates of time constants were obtained for both the switch from low- to high-contrast context (τL→H) and the switch from high- to low-contrast context (τH→L) for 18 units. Adaptation to high-contrast context occurred with a median τL→H of 86 ms, compared with a slower adaptation to low-contrast context with a median τH→L of 157 ms. This difference was significant (p < 0.001, sign-rank) and evident for 14/18 of the individual

units ( Figure 6F). Thus, the time courses for increases and decreases in neural gain are asymmetric. To explore the mechanism for gain control, we asked whether gain is modulated

by the contrast within Pomalidomide a local region of frequency space or whether it is a function of the global statistics of the input. To address this, we varied the contrast of the DRC stimuli within two separate frequency regions. One region was denoted the “test,” centered around a chosen unit’s BF and spanning 0.5, 0.67, or 1.2 octaves. The remaining frequency bands were denoted Sorafenib the “mask” (Figure 7A). We aimed to situate the test stimulus over the “responsive frequency range” (ΦRFΦRF; see Experimental Procedures), the frequencies to which a given neuron (linearly) responded. However, since we recorded multiple units simultaneously (usually bilaterally), we actually sampled a range of conditions where the test stimulus covered the neuron’s responsive frequency range, overlapped it, or lay entirely outside it. This enabled us to measure how contrast gain depended on the amount of overlap between the test stimulus and ΦRFΦRF. We presented nine separate DRCs, where the contrasts in the test (σtest  ) and mask (σmask  ) were independently chosen from σL   = 2.9 dB, 5.8 dB, or 8.7 dB (c =   33%, 64%, or 92%).

TCL We found that the gain of each neuron was most strongly modulated by contrast within the responsive frequency range. Thus, varying σtest   had the strongest effect on gain when the test stimulus completely covered ΦRFΦRF ( Figure 7B). Similarly, varying σmask   had the strongest effect when the mask completely covered ΦRFΦRF ( Figure 7C). However, contrast away from the responsive frequency range also had an impact on gain. For example, even when the test stimulus completely covered ΦRFΦRF, decreasing σmask   still resulted in an increase in gain ( Figure 7C). There were also interactions between contrast within and outside ΦRFΦRF (compare Figure 7B with 7D and Figure 7C with 7E). This is summarized in Figure 7F for 24 units where the test completely covered ΦRFΦRF.

50 and 52 In young diabetic patients, antioxidant intake abolishe

50 and 52 In young diabetic patients, antioxidant intake abolished the activation of molecular regulators of endogenous antioxidant enzymes by a moderate exercise regimen.53APOE4 has been associated with lower antioxidant activity, 74 decreased capacity to remove by-products of oxidative stress 75 and increased oxidative stress. 76 Therefore, a combination of antioxidants to lower oxidative stress and exercise to boost antioxidant defenses should lead to a further improvement than each intervention this website independently. Our study did not reveal such a beneficial additive interaction; in fact most effects observed with the

combined Treatment mimicked the effects seen with exercise. The lack of an additive/synergistic effect on cognitive function may have been due to reaching a maximum ceiling of performance. While each intervention independently improved the performance of the mice, it may have improved to a maximal level of performance and further

improvements by combining Treatments cannot be detected. Further studies will be needed to determine whether the combination had an additive/synergistic effect at the molecular level which did not translate to further improvements due to a ceiling effect being reached. Even though the effects were minor and in select domains of cognition, our study supported previous reports of APOE4 mice performing better than APOE3 mice at a young age. While the beneficial effect of exercise training on learning and cognitive flexibility was found in both genotype and in both males and females, the beneficial

EPZ-6438 research buy effect of antioxidant supplementation seemed to be genotype dependent. Lastly, in young adult mice the combination of exercise and antioxidant did not lead to additive or antagonistic effects. This research was supported by grant NIRG-10-173988 and donation from the Pine Family Foundation. “
“Women that enter menopause prematurely, or before the age of 40, due to bilateral oophorectomy incur a doubled lifetime risk of dementia and a 5-fold increased risk of mortality from neurological disorders.1 and 2 The molecular mechanisms underlying the enhanced risks remain poorly understood, but prolonged loss of the neuroprotective ovarian steroid hormone 17β-estradiol (E2 or Sclareol estrogen) is thought to play a key role, as estrogen therapy administered at the time of surgery and continued until the median age of natural menopausal onset normalizes these risks.3 Studies in our lab have provided a potential clue as to why surgical menopause may lead to an increased risk of dementia and mortality from neurological disorders. Along these lines, recent work has shown that the hippocampus sustains more damage from global cerebral ischemia (GCI) following 10-week ovariectomy (long-term E2 deprivation (LTED)); this includes previously unseen neuronal cell death in the hippocampal CA3 region, which is usually highly resistant to GCI, and a worse cognitive outcome following GCI.

, 2009) The vast majority of these cells are PV+ FS interneurons

, 2009). The vast majority of these cells are PV+ FS interneurons and calbindin (CB)-expressing LTS interneurons but only rarely CR+ interneurons; it is estimated that up to 60% of PV+, 25% of CB+, and <10% of CR+ interneurons express D1 receptors (Le Moine and Gaspar, 1998). The fraction of interneurons expressing D1-like receptors may be larger, as D5 receptors complement the expression pattern of D1 receptors, labeling mostly

CR+ interneurons, and less so PV+ interneurons (Glausier et al., 2009). By contrast, D2 receptors distribute to a comparatively smaller fraction of cortical GABAergic interneurons: only 5%–17% of interneurons contain D2 receptor mRNA (Santana et al., 2009), the majority of which consist of PV+ interneurons (Le Moine and Gaspar, 1998). Although D3 and D4

receptors Epigenetics inhibitor may complement the expression of D2 receptors in cortical interneurons, their overall distribution is limited (Khan et al., 1998), indicating that D2-like receptors are unlikely to distribute to a large proportion of GABAergic check details interneurons. Transgenic mice have the potential to help identify cortical cells with transcriptionally active DA receptor genes. However, currently available transgenic lines for D1 and D2 receptors were selected based on the fidelity of transgene expression in striatal neurons (Valjent et al., 2009). Comparatively little is known in cortex regarding the penetrance and specificity of these transgenes in D1 and D2 receptor-expressing neurons. A recent study by Zhang

et al. (2010) determined that Drd2-EGFP/Drd1a-tdTomato BAC transgenic mice express EGFP in over 90% of PFC pyramidal neurons and tdTomato in 16%–25% of pyramidal cells, most of which coexpress EGFP, without any region or layer-specific differences. This distribution stands in stark contrast Carnitine dehydrogenase to that described previously ( Bentivoglio and Morelli, 2005). In another recent study ( Gee et al., 2012), PFC pyramidal neurons identified in Drd2-EGFP and Drd2-Cre BAC transgenic mice were found to project to thalamus but not contralateral cortex, unlike previous descriptions using in situ hybridization ( Gaspar et al., 1995). These discrepancies probably speak to the weaknesses of both histological and transgenic approaches. BAC transgenes are generated by nonspecific integration into the target genome and are not immune to positional effects, requiring phenotypic characterization of several transgenic lines before identifying the ones that most closely recapitulate endogenous gene expression patterns. Moreover, transgenic reporter and effector proteins are not subject to the same posttranscriptional and homeostatic regulatory mechanisms that control GPCR expression and may therefore highlight cells that do not functionally detect DA under normal conditions. Conversely, low-abundance GPCR transcripts may be functionally relevant but below the detection limit of conventional histological methods.

The AS event generating

The AS event generating HDAC inhibitor the Gls-l and Gls-s isoforms was listed as a top target in our Aspire2 AS analysis, with a validated ΔI of −0.3, (Figure 6B and Table S7). Quantitative RT-PCR using primers specific for each Gls isoform demonstrated that in Elavl3−/−;Elavl4−/− DKO brain, abundance of the Gls-s isoform did not change while abundance of the Gls1-l isoform was reduced to approximately 50% of the WT levels ( Figure 6D). Western blot analysis using an antibody recognizing a common epitope to both isoforms also demonstrated that the abundance of Gls-s and Gls-l proteins were reduced to 60% and 25% of the WT levels, respectively ( Figures

6C and 6E). Since Elavl3/4 DKO die at age P0 it is difficult to further carry out any physiological analyses. We assessed whether Elavl3−/− single KO mice also exhibited a defect in glutamate regulation and observed a smaller but significant decrease in

total glutamate levels and in Gls-l, but not Gls-s, protein levels ( Figure S5). These results point to a role for nElavl proteins in directly controlling Gls-s and Selleckchem Obeticholic Acid Gls-l levels in the nervous system through reinforcing mechanisms of involving both the regulation of AS and mRNA half-life, consistent with nElavl HITS-CLIP results demonstrating direct binding to both intronic and 3′UTR elements. To assess whether there might be a physiologic correlate of excitation/inhibition imbalance manifested by misregulation of glutamate signaling in Elavl3−/− mice, we undertook an EEG analysis of cortical function. Video EEG monitoring of awake and behaving mutants revealed a striking pattern of abnormal cortical hypersynchronization in both Elavl3+/− and Elavl3−/− mice never seen in WT mice ( Figure 7A; Carnitine dehydrogenase Movie S1). In Elavl3+/− mice, there was a nearly continuous presence (1–9/min) of bilaterally synchronous sharp cortical

spike discharges, sometimes accompanied by brief afterdischarges ( Figure 7B). Elavl3−/− mice displayed similar discharges as well as more severe, non-convulsive electrographic seizures lasting from 10–30 s ( Figure 7C). Both patterns demonstrate aberrant hypersynchronization in cortical networks. Until recently studies aimed at identifying regulatory RNA sequences have been limited to correlative information lacking direct functional links to biological processes. HITS-CLIP technique provides a methodology to identify such functional RNA-protein interaction sites and has been successfully applied to identifying binding sites and uncovering new biological functions for several RNABPs, including Nova (Licatalosi et al., 2008), PTB (Xue et al., 2009), hnRNP C (König et al., 2010), TIA-1 (Wang et al., 2010b), TDP-43, and Fox2 (Yeo et al., 2009).

Afferent stimulus strengths were adjusted in these experiments so

Afferent stimulus strengths were adjusted in these experiments so that bilateral EPSPs remained subthreshold (Figures S3A and S3C). In both the absence and presence of inhibition, subthreshold summation was remarkably linear, nearly matching the summation predicted from the arithmetic sums of average PSP waveforms (Figures 6E and 6F). ITD functions were generated by measuring the maximal depolarization attained during each coincidence trial

(Figures S3B and S3D). Lacking a MEK pathway threshold mechanism to select for the largest events, subthreshold ITD functions were broader and flatter than spike-based ITD functions. Similar to the spiking responses, inhibition did not alter the mean or median mass of ITD functions (Figures S3E and S3F), whereas physiological inhibition and its hyperpolarizing component significantly decreased the peak and half-width of subthreshold ITD functions (Figures S3G and S3H). These results suggest that the effects of inhibition on spike probability ITD functions are a direct reflection of how inhibition shapes subthreshold summation. ITD computations are usually made within the phase-locking range of input neurons, which extends up to ∼2 kHz (Johnson, 1980; Joris et al., 1994). Given that even brief

sounds generate multiple stimulus cycles, the duration of IPSPs suggests Selleck ZVADFMK that they will sum at higher frequencies, possibly complicating synaptic coincidence detection. To test whether IPSPs sum, we recorded from MSO neurons while using stimulating electrodes to evoke 100–800 Hz trains of ten ipsilateral or contralateral IPSPs. Both ipsilateral and contralateral IPSPs showed clear evidence of temporal summation (Figures 7A and 7B). We quantified Florfenicol this by measuring the amount the membrane potential was hyperpolarized relative to rest at the foot of each IPSP and comparing this to the peak amplitude of the first IPSP in the train. This showed that there was significant summation of ipsilateral IPSPs at frequencies of 300 Hz and greater (Figure 7C) and of contralateral IPSPs at frequencies of 200 Hz and greater (Figure 7D).

Under in vivo conditions, in which inhibition is presumably binaural and subject to more temporal jitter than observed with local afferent stimulation in slice, the summation of IPSPs is probably even greater than observed here. The presence of this summation suggests that IPSPs occurring later in a train will contribute to the temporal dynamics of coincidence detection differently than earlier IPSPs. We also examined how the peak amplitudes of IPSPs, as measured from the foot to the peak of each event, varied during the train relative to the amplitude of the first event. Previous studies have found that IPSCs undergo significant short-term depression during repetitive stimuli at frequencies as low as 0.5 Hz (Couchman et al., 2010; Fischl et al., 2012).

The result did not change when we evaluated the various subcatego

The result did not change when we evaluated the various subcategories of rare X-linked CNVs including exonic, deletions, duplications, size, brain-expressed, or

ASD-associated. We next considered whether the absence of association of rare transmitted CNVs might be a consequence of an inability to differentiate functional from neutral variants. We looked selleckchem to pathway analyses to help address this question, reasoning that if the specific genic content of CNVs contributed to disease risk, we would find a greater enrichment of biological pathways in probands compared to their unaffected siblings. We used two gene ontology and pathway analysis tools, MetaCore from GeneGo, Inc. and DAVID (Dennis et al., 2003 and Huang selleck chemical et al., 2009), to analyze 1516 genes within CNVs exclusive to probands and 1357 genes exclusive to siblings. The total number and size of rare transmitted CNVs used to determine these gene sets were highly similar in probands and siblings (Figure 5). GeneGo networks identified 22 pathways showing significant enrichment in probands versus only four enriched pathways among siblings. This difference was significant based on 100 permutations of the data set (p = 0.04). DAVID yielded consistent results with 59 pathways enriched in probands and 19 in siblings (p = 0.01, permutation analysis) (Figure 6). For the present study, we elected

to restrict our evaluation of pathways to the general question described here. A manuscript that is in preparation describes a more extensive analysis, focusing on both structural and gene expression data from the SSC. We next examined all rare CNVs in the SSC in light of previously reported findings, comparing our data to the list of ASD regions included in the recent AGP analysis (Pinto et al., 2010). We also considered genes implicated by recent common variant studies, including SEMA5A ( Weiss et al., 2009), MACROD2 (

Anney et al., 2010), CDH9 and CDH10 ( Wang et al., 2009), the MET oncogene Carnitine palmitoyltransferase II ( Campbell et al., 2006), EN2 ( Gharani et al., 2004), as well as selected schizophrenia loci ( International Schizophrenia Consortium, 2008, McCarthy et al., 2009, Millar et al., 2000, Stefansson et al., 2008, Walsh et al., 2008 and Xu et al., 2008) ( Table 3). We identified multiple regions in which rare transmitted and/or rare de novo events corresponded to previously characterized loci in both ASD and schizophrenia. Finally, we looked for evidence of association for all CNVs in the SSC sample, common or rare, transmitted or de novo, evaluating all high-confidence autosomal CNVs together with all confirmed de novo CNVs. In this instance, we did not use a frequency cutoff to define a set of rare transmitted events. A total of 3667 recurrent regions were identified; 6 showed relative enrichment in probands and 5 showed relative enrichment in siblings. No result reached significance after correction for multiple comparisons (Table S7 and Figure 7C).

Within each geographic area

Within each geographic area JQ1 cell line we group children into

five wealth quintiles based on asset index [23]. As a result, the modeling unit of analysis is geographic area × wealth quintile × sex. Future outcomes are discounted at 3% and costs are estimated in 2013 US dollars. Overall estimates of rotavirus Modulators mortality by region, state and sex are taken from Morris et al. [14] (Table 1). However it is likely that there is substantial heterogeneity in rotavirus mortality risk within these groups due to differential nutritional status and access to basic care for diarrheal disease, based on socio-economic status. As a result, we developed an evidence-based individual risk index to estimate the relative distribution of mortality within these region-sex populations. We used data from the 2005 to 2006 India National Family Health Survey III (NFHS-3) [24] to calculate individual risk index values as well as mean values for each subpopulation, accounting for complex survey design in Stata (version 12) [25]. The risk index assumes that an individual child’s risk of rotavirus mortality is

a function of the child’s nutritional status (as measured by weight-for-age) and the likelihood of receiving rehydration if he/she experiences a diarrheal event. The existing literature suggests that both factors are strongly and quantitatively linked to diarrheal mortality (although not specifically rotavirus mortality) [15] and [26].

A nutritional risk factor was ABT-737 cell line developed for each child based on their weight for age and a linearized estimate of relative risk from Caulfield et al. [15] (WFAi). Since data on rehydration is only available for children with an episode of diarrhea in the previous 2 weeks we estimated the individual propensity for receiving rehydration by fitting a logistic regression model to predict rehydration based on age, asset index score, gender and state. We then used the PREDICT function in Stata these (version 12) [25] to estimate the propensity for all children (PrORSi). The individual risk factor for rehydration was calculated for each child as the product of their propensity score and 0.07 (βORS), based on the estimated 93% effectiveness of appropriate rehydration from Munos et al. [26]. For each region (r) wealth quintile (q) and sex (s) sub-population, the mean risk index was calculated based on Equation (1). equation(1) RVRiskIndexr,q,s=∑iNr,q,sβORS⋅PrORSi⋅WFAiNr,q,s In order to test this individual risk model, we examined the correlation between state-wide averages generated as described above, with the statewide mortality estimates from Morris et al. [14]. In order to estimate the distribution of rotavirus mortality within geographic-economic-gender subpopulations we combined the risk index and the mortality estimates by geographic area and gender from Morris et al. [14].