Still in Search for an EAAT Activator: GT949 Does Not Activate EAAT2, nor EAAT3 in Impedance and Radioligand Uptake Assays

Excitatory amino acid transporters (EAATs) are important regulators of amino acid transport and in particular glutamate. Recently, more interest has arisen in these transporters in the context of neurodegenerative diseases. This calls for ways to modulate these targets to drive glutamate transport, EAAT2 and EAAT3 in particular. Several inhibitors (competitive and noncompetitive) exist to block glutamate transport; however, activators remain scarce. Recently, GT949 was proposed as a selective activator of EAAT2, as tested in a radioligand uptake assay. In the presented research, we aimed to validate the use of GT949 to activate EAAT2-driven glutamate transport by applying an innovative, impedance-based, whole-cell assay (xCELLigence). A broad range of GT949 concentrations in a variety of cellular environments were tested in this assay. As expected, no activation of EAAT3 could be detected. Yet, surprisingly, no biological activation of GT949 on EAAT2 could be observed in this assay either. To validate whether the impedance-based assay was not suited to pick up increased glutamate uptake or if the compound might not induce activation in this setup, we performed radioligand uptake assays. Two setups were utilized; a novel method compared to previously published research, and in a reproducible fashion copying the methods used in the existing literature. Nonetheless, activation of neither EAAT2 nor EAAT3 could be observed in these assays. Furthermore, no evidence of GT949 binding or stabilization of purified EAAT2 could be observed in a thermal shift assay. To conclude, based on experimental evidence in the present study GT949 requires specific assay conditions, which are difficult to reproduce, and the compound cannot simply be classified as an activator of EAAT2 based on the presented evidence. Hence, further research is required to develop the tools needed to identify new EAAT modulators and use their potential as a therapeutic target.

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities

Cancer remains a leading cause of mortality worldwide and calls for novel therapeutic targets. Membrane proteins are key players in various cancer types but present unique challenges compared to soluble proteins. The advent of computational drug discovery tools offers a promising approach to address these challenges, allowing for the prioritization of "wet-lab" experiments. In this review, we explore the applications of computational approaches in membrane protein oncological characterization, particularly focusing on three prominent membrane protein families: receptor tyrosine kinases (RTKs), G protein-coupled receptors (GPCRs), and solute carrier proteins (SLCs). We chose these families due to their varying levels of understanding and research data availability, which leads to distinct challenges and opportunities for computational analysis. We discuss the utilization of multi-omics data, machine learning, and structure-based methods to investigate aberrant protein functionalities associated with cancer progression within each family. Moreover, we highlight the importance of considering the broader cellular context and, in particular, cross-talk between proteins. Despite existing challenges, computational tools hold promise in dissecting membrane protein dysregulation in cancer. With advancing computational capabilities and data resources, these tools are poised to play a pivotal role in identifying and prioritizing membrane proteins as personalized anticancer targets.

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.

Emerging Hyalomma lusitanicum: From identification to vectorial role and integrated control

In the Mediterranean basin, the tick species Hyalomma lusitanicum Koch stands out among other species of the Hyalomma genus due to its wide distribution, and there is great concern about its potential role as a vector and/or reservoir and its continuous expansion to new areas because of climate warming and human and other animal movements. This review aims to consolidate all the information on H. lusitanicum, including taxonomy and evolution, morphological and molecular identification, life cycle, sampling methods, rearing under laboratory conditions, ecology, hosts, geographical distribution, seasonality, vector role and control methods. The availability of adequate data is extremely relevant to the development of appropriate control strategies in areas where this tick is currently distributed as well as in new areas where it could become established in the near future.

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors

Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features are computed to describe small molecules and proteins, which directly impact the quality of the predictive models. State-of-the-art protein descriptors, however, are calculated from the protein sequence and neglect the dynamic nature of proteins. This dynamic nature can be computationally simulated with molecular dynamics (MD). Here, novel 3D dynamic protein descriptors (3DDPDs) were designed to be applied in bioactivity prediction tasks with PCM models. As a test case, publicly available G protein-coupled receptor (GPCR) MD data from GPCRmd was used. GPCRs are membrane-bound proteins, which are activated by hormones and neurotransmitters, and constitute an important target family for drug discovery. GPCRs exist in different conformational states that allow the transmission of diverse signals and that can be modified by ligand interactions, among other factors. To translate the MD-encoded protein dynamics two types of 3DDPDs were considered: one-hot encoded residue-specific (rs) and embedding-like protein-specific (ps) 3DDPDs. The descriptors were developed by calculating distributions of trajectory coordinates and partial charges, applying dimensionality reduction, and subsequently condensing them into vectors per residue or protein, respectively. 3DDPDs were benchmarked on several PCM tasks against state-of-the-art non-dynamic protein descriptors. Our rs- and ps3DDPDs outperformed non-dynamic descriptors in regression tasks using a temporal split and showed comparable performance with a random split and in all classification tasks. Combinations of non-dynamic descriptors with 3DDPDs did not result in increased performance. Finally, the power of 3DDPDs to capture dynamic fluctuations in mutant GPCRs was explored. The results presented here show the potential of including protein dynamic information on machine learning tasks, specifically bioactivity prediction, and open opportunities for applications in drug discovery, including oncology.

Invariant representations in deep learning for optoacoustic imaging

Image reconstruction in optoacoustic tomography (OAT) is a trending learning task highly dependent on measured physical magnitudes present at sensing time. A large number of different settings and also the presence of uncertainties or partial knowledge of parameters can lead to reconstruction algorithms that are specifically tailored and designed to a particular configuration, which could not be the one that will ultimately be faced in a final practical situation. Being able to learn reconstruction algorithms that are robust to different environments (e.g., the different OAT image reconstruction settings) or invariant to such environments is highly valuable because it allows us to focus on what truly matters for the application at hand and discard what are considered spurious features. In this work, we explore the use of deep learning algorithms based on learning invariant and robust representations for the OAT inverse problem. In particular, we consider the application of the ANDMask scheme due to its easy adaptation to the OAT problem. Numerical experiments are conducted showing that when out-of-distribution generalization (against variations in parameters such as the location of the sensors) is imposed, there is no degradation of the performance and, in some cases, it is even possible to achieve improvements with respect to standard deep learning approaches where invariance robustness is not explicitly considered.

Oncological drug discovery: AI meets structure-based computational research

The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the diversity of neoplastic diseases portrayed by the different hallmarks of cancer. Here, we review six use case scenarios for integrated computational methods, namely driver prediction, computational mutagenesis, (off)-target prediction, binding site prediction, virtual screening, and allosteric modulation analysis. We address the heterogeneity of integration approaches and individual methods, while acknowledging their current limitations and highlighting their potential to bring drugs for personalized oncological therapies to the market faster.

On the robustness of model-based algorithms for photoacoustic tomography: Comparison between time and frequency domains

For photoacoustic image reconstruction, certain parameters such as sensor positions and speed of sound have a major impact on the reconstruction process and must be carefully determined before data acquisition. Uncertainties in these parameters can lead to errors produced by a modeling mismatch, hindering the reconstruction process and severely affecting the resulting image quality. Therefore, in this work, we study how modeling errors arising from uncertainty in sensor locations affect the images obtained by matrix model-based reconstruction algorithms based on time domain and frequency domain models of the photoacoustic problem. The effects on the reconstruction performance with respect to the uncertainty in the knowledge of the sensors location are compared and analyzed both in a qualitative and quantitative fashion for both time and frequency models. Ultimately, our study shows that the frequency domain approach is more sensitive to this kind of modeling errors. These conclusions are supported by numerical experiments and a theoretical sensitivity analysis of the mathematical operator for the direct problem.

Seasonal Dynamics of Fleas (Siphonaptera: Pulicidae, Ceratophyllidae and Leptopsyllidae) on Oryctolagus cuniculus in a Meso-Mediterranean Area of Central Spain

Flea infestations of wild rabbits were examined monthly in central Spain in a meso-Mediterranean area for 5 yr. A total of 1,180 wild rabbits were trapped and 7,022 fleas were collected from them. Overall, the prevalence was 74.1% with a mean flea index of 5.95 fleas per rabbit. Four flea species were identified: Spilopsyllus cuniculi (Dale, 1878) was the most abundant species (accounting for 74.3% of fleas collected) followed by Xenopsylla cunicularis (Smit, 1957), Odontopsyllus quirosi (Gil Collado, 1934), and Nosopsyllus fasciatus (Bosc, 1800) (18.9, 6.7, and 0.1%, respectively). The highest prevalence was observed in S. cuniculi (48.6%) followed by X. cunicularis, O. quirosi, and N. fasciatus (34.3, 20.0, and 0.6%, respectively). Odontopsyllus quirosi and S. cuniculi were mainly collected from autumn to spring with the peak of infestation in winter, while X. cunicularis was mainly found from spring to autumn with maximum levels of infestation during the summer months. The relevance of these findings is discussed.

A method for the calibration of wideband ultrasonic sensors for optoacoustics

A method for calibration of ultrasonic sensors for optoacoustics that provides both frequency response and sensitivity is presented. In order to obtain the bandwidth and the frequency response of an uncalibrated sensor, a point source with broadband spectra generated by a laser-induced bubble on a copper wire submerged in water is employed. On the other hand, the sensitivity measurement relies on the spatial symmetry of the pressure pulse and on a calibrated transducer. Therefore, two sensors are employed to detect the pressure pulse at the same distance from the source. The symmetry of the acoustic field that arrives at both transducers is adjusted and verified by means of an optical interferometer that provides a null signal when the copper wire is placed at the right position. The method is tested on the characterization of a thin-film polymeric piezoelectric transducer with a cylindrical focused shape.

Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors

Kinases are frequently studied in the context of anticancer drugs. Their involvement in cell responses, such as proliferation, differentiation, and apoptosis, makes them interesting subjects in multitarget drug design. In this study, a workflow is presented that models the bioactivity spectra for two panels of kinases: (1) inhibition of RET, BRAF, SRC, and S6K, while avoiding inhibition of MKNK1, TTK, ERK8, PDK1, and PAK3, and (2) inhibition of AURKA, PAK1, FGFR1, and LKB1, while avoiding inhibition of PAK3, TAK1, and PIK3CA. Both statistical and structure-based models were included, which were thoroughly benchmarked and optimized. A virtual screening was performed to test the workflow for one of the main targets, RET kinase. This resulted in 5 novel and chemically dissimilar RET inhibitors with remaining RET activity of <60% (at a concentration of 10 μM) and similarities with known RET inhibitors from 0.18 to 0.29 (Tanimoto, ECFP6). The four more potent inhibitors were assessed in a concentration range and proved to be modestly active with a pIC₅₀ value of 5.1 for the most active compound. The experimental validation of inhibitors for RET strongly indicates that the multitarget workflow is able to detect novel inhibitors for kinases, and hence, this workflow can potentially be applied in polypharmacology modeling. We conclude that this approach can identify new chemical matter for existing targets. Moreover, this workflow can easily be applied to other targets as well.

Generation of sub-microsecond quasi-unipolar pressure pulses

We present a method to generate sub-microsecond quasi-unipolar pressure pulses. Our approach is based on the laser irradiation of a thin copper wire submerged in water. The acoustic waveforms were recorded using two different, well characterized, wideband detection techniques: piezoelectric and optical interferometry. The results show that the irradiated target behaves as an omnidirectional source. Moreover, the peak pulse pressure linearly depends on the laser fluence and the source size. From the results, we propose an empirical equation for the spatial and temporal profile of the pressure pulse. The method has several advantages: ease of implementation, high repeatability, wide ultrasonic bandwidth and quasi-unipolar time profile. These features lead to potential applications of this acoustic source in ultrasonic characterization such as transducer systems, materials or passive devices.

Spirocercosis in red fox (Vulpes vulpes) in a natural reserve located in a meso-Mediterranean area

Spirocerca lupi Rudolphi 1809 (Nematoda Spirocercidae) has an indirect cycle involving intermediate and paratenic hosts, having domestic or wild canids as the main definitive hosts. The most frequent pathology affecting dogs is a granulomatous tumor-like growth containing adults in the oesophagus and aorta. There are very few references about the presence of nodules in the stomach. There is scant information about the epidemiology of this disease in wild red foxes in meso-Mediterranean areas. In this work we report on the natural infection of wild red foxes by Spirocerca lupi and the damage produced in the stomach wall in an area where contact with other potential definitive hosts (canids) is very rare. From July 2015 to November 2016, 61 red foxes were sampled. 18.03% of the stomach walls examined had nodules containing Spirocerca lupi adults and eggs. The prevalence of infection was similar for young and adult groups (23.81 and 18.18%; χ2 = 0.25; df = 1; P = 0.6171) and it was higher in females than in males (25.81 versus 10.00%, χ² = 2.58; df = 1; P = 0.1082). The red fox population in the area seems to be well established judging from their age distribution and the fact that they could be captured all year round. It would appear that in the absence of other main definitive host S. lupi population is able to survive just parasitizing red foxes. Pathologic effects of this parasite on red foxes seems to show some differences related to domestic dogs. These results also indicates as predator control programs can maintain suitable host populations with reduced level of infection.

Parametric modeling of wideband piezoelectric polymer sensors: Design for optoacoustic applications

In this work, we present a three-dimensional model for the design of wideband piezoelectric polymer sensors which includes the geometry and the properties of the transducer materials. The model uses FFT and numerical integration techniques in an explicit, semi-analytical approach. To validate the model, we made electrical and mechanical measurements on homemade sensors for optoacoustic applications. Each device was implemented using a polyvinylidene fluoride thin film piezoelectric polymer with a thickness of 25 μm. The sensors had detection areas in the range between 0.5 mm² and 35 mm² and were excited by acoustic pressure pulses of 5 ns (FWHM) from a source with a diameter around 10 μm. The experimental data obtained from the measurements agree well with the model results. We discuss the relative importance of the sensor design parameters for optoacoustic applications and we provide guidelines for the optimization of devices.

Modeling thin-film piezoelectric polymer ultrasonic sensors

This paper presents a model suitable to design and characterize broadband thin film sensors based on piezoelectric polymers. The aim is to describe adequately the sensor behavior, with a reasonable number of parameters and based on well-known physical equations. The mechanical variables are described by an acoustic transmission line. The electrical behavior is described by the quasi-static approximation, given the large difference between the velocities of propagation of the electrical and mechanical disturbances. The line parameters include the effects of the elastic and electrical properties of the material. The model was validated with measurements of a poly(vinylidene flouride) sensor designed for short-pulse detection. The model variables were calculated from the properties of the polymer at frequencies between 100 Hz and 30 MHz and at temperatures between 283 K and 313 K, a relevant range for applications in biology and medicine. The simulations agree very well with the experimental data, predicting satisfactorily the influence of temperature and the dielectric properties of the polymer on the behavior of the sensor. Conversely, the model allowed the calculation of the material dielectric properties from the measured response of the sensor, with good agreement with the published values.

Stereodynamics of the photodissociation of nitromethane at 193 nm: unravelling the dissociation mechanism

The photodissociation of nitromethane at 193 nm is reviewed in terms of new stereodynamical information provided by the measurement of the first four Dixon's bipolar moments, β0(2)(20), β0(0)(22), β0(2)(02), and β0(2)(22), using slice imaging. The measured speed-dependent β0(2)(20) (directly related with the spatial anisotropy parameter β) indicates that after one-photon absorption to the S3(2 (1)A″) state by an allowed perpendicular transition, two reaction pathways can compete with similar probability, a direct dissociation process yielding ground-state CH3 and NO2(1 (2)A2) radicals and a indirect dissociation through conical intersections in which NO2 radicals are formed in lower-lying electronic states. A particularly important result from our measurements is that the low recoil energy part of the methyl fragment translational energy distribution presents a contribution with parallel character, irrespective of the experimental conditions employed, that we attribute to parent cluster dissociation. Moreover, the positive values found for the β0(0)(22) bipolar moment indicates some propensity for the fragment's recoil velocity and angular momentum vectors to be parallel.

Photodissociation of pyrrole-ammonia clusters below 218 nm: quenching of statistical decomposition pathways under clustering conditions

The excited state hydrogen transfer (ESHT) reaction in pyrrole-ammonia clusters (PyH·(NH(3))(n), n = 2-5) at excitation wavelengths below 218 nm down to 199 nm, has been studied using a combination of velocity map imaging and non-resonant detection of the NH(4)(NH(3))(n-1) products. Special care has been taken to avoid evaporation of solvent molecules from the excited clusters by controlling the intensity of both the excitation and probing lasers. The high resolution translational energy distributions obtained are analyzed on the base of an impulsive mechanism for the hydrogen transfer, which mimics the direct N-H bond dissociation of the bare pyrrole. In spite of the low dissociation wavelengths attained (~200 nm) no evidence of hydrogen-loss statistical dynamics has been observed. The effects of clustering of pyrrole with ammonia molecules on the possible statistical decomposition channels of the bare pyrrole are discussed.

Slice imaging and wave packet study of the photodissociation of CH3I in the blue edge of the A-band: evidence of reverse 3Q0 ← 1Q1 non-adiabatic dynamics

The photodissociation of CH(3)I in the blue edge (217-230 nm) of the A-band has been studied using a combination of slice imaging and resonance enhanced multiphoton ionization (REMPI) detection of the CH(3) fragment in the vibrational ground state (ν = 0). The profiles of the CH(3) (ν = 0) kinetic energy distributions and the photofragment anisotropies are interpreted in terms of the contribution of the excited surfaces involved in the photodissociation process, as well as the probability of non-adiabatic curve crossing between the (3)Q(0) and (1)Q(1) states. In the studied region, unlike in the central part of the A-band where absorption to the (3)Q(0) state dominates, the I((2)P(J)), with J = 1/2, 3/2, in correlation with CH(3) (ν = 0) kinetic energy distributions show clearly two contributions of different anisotropy, signature of the competing adiabatic and non-adiabatic dynamics, whose ratio strongly depends on the photolysis wavelength. The experimental results are compared with multisurface wave packet calculations carried out using the available ab initio potential energy surfaces, transition moments, and non-adiabatic couplings, employing a reduced dimensionality model. A good qualitative agreement is found between experiment and theory and both show evidence of reverse (3)Q(0)←(1)Q(1) non-adiabatic dynamics at the bluest excitation wavelengths both in the fragment kinetic energy and angular distributions.

Background subtraction in pulsed photoacoustics through neural-network processing

We report on the application of neural-network processing to pulsed photoacoustics for improving the detection limit by subtracting the window-heating-associated background. This technique was applied to the measurement of ethylene traces excited by a TEA (transverse electrical discharge in gas at atmospheric pressure) CO(2) laser. The signal contains a term that shows absorption saturation, characteristic of the absorbing gas, and another, generated by window heating, linearly dependent on laser energy. At low concentrations, normalization to laser energy is not possible owing to the different absorption mechanisms. To overcome this problem we relied on a neural-network filter, trained with experimentally obtained patterns, that subtracts the background and returns the sample concentration. This way, we reduced the detection limit to 20% of the previous limit obtained by reading the main resonance peak amplitude.

Evaluation of the quality of the water in El Hondo natural park located in the east of Spain

The purpose of the present work was to evaluate the quality of the water in El Hondo Park, an important wetland located in the east of Spain (province of Alicante) and included on the Ramsar List. The influence of the input of pollutants was assessed over a 14-month period in order to propose remedial action. Three different sources of waters were studied: irrigation water, brackish water and reservoir water. The irrigation water was found to have a high value of conductivity with high concentrations of Cl-, SO(4)2-, Na+ and K+ due to the influence of the brackish water. The concentration of organic matter given as CODT (total chemical oxygen demand) was found to be in the range of 70-600 mg/L of CODT, which was comparable to low-middle strength wastewater. A high concentration of Chlorophyll (a) was found in samples of reservoir water and the eutrophication of this water was thus observed. A high linear relationship was found among CODT, CODF (filtered COD) and BOD5; among electrical conductivity (E.C.), Cl-, SO4(-2), Na+, K+, Ca2+ and Mg2+ and among pH, CO3H- and CO(3)2- in all the samples evaluated. Taking this fact into consideration, a simplified water quality index (WQI) was calculated. Using this parameter, the quality of the water from different sources and its variation during the period evaluated was determined to be at a maximum during the months of December to February, which coincided with the period of high precipitations and low temperature. The highest values of this parameter were found in the samples corresponding to the reservoir water while the lowest values were found in the samples of the brackish water. By determination of the WQI, the influence of the brackish water on the quality of water for irrigation and reservoir waters was confirmed.

Myeloid mixed chimerism is associated with relapse in bcr-abl positive patients after unmanipulated allogeneic bone marrow transplantation for chronic myelogenous leukemia

BACKGROUND AND OBJECTIVE

Although bcr-abl polymerase chain reaction (PCR) positivity after bone marrow transplantation (BMT) for chronic myelogenous leukemia (CML) is significantly related to relapse, the predictive value of the assay is not very high and therefore most investigators consider that qualitative RT-PCR data alone are too imprecise to enable clinical decisions to be taken in individual cases. To define the clinical outcome of bcr-abl positive patients after unmanipulated BMT better, we sought the origin of hematopoiesis and traced its evolution over time.

DESIGN AND METHODS

Forty-nine patients received allogeneic BMT for CML (39 in chronic phase and 10 in accelerated phase/blast crisis). Median follow-up was 61 months (range 4-92). mRNA and DNA were used to assess bcr-abl and chimerism status respectively. Quantitative VNTR-PCR on total cells and lymphoid or myeloid population allowed us to assign and measure the origin of hematopoiesis.

RESULTS

Both bcr-abl positivity and the presence of mixed chimerism (MC) were significantly associated with relapse (p = 0.0009 and p < 0.0001 respectively). Relapse was observed in one of 39 patients with complete donor chimerism and in 6 of 9 patients with MC. These six cases showed increasing levels of host hemopoiesis and bcr-abl positivity in the CD15-positive population prior to relapse. The other three cases had decreasing or stable low-level MC which was restricted to the T-cells as well as bcr-abl negativity.

INTERPRETATION AND CONCLUSIONS

Whereas the simple detection of bcr-abl fails to identify patients who will relapse with certainty, the assessment of MC by VNTR-PCR does identify patients headed to relapse. Confirmation of myeloid involvement and increasing levels over time further elucidates the clinical outcome of bcr-abl positive patients after BMT.

Increasing mixed haematopoietic chimaerism after BMT with total depletion of CD4+ and partial depletion of CD8+ lymphocytes is associated with a higher incidence of relapse

In this study we analysed the incidence and clinical impact of the persistence of host haemopoiesis (mixed chimaerism, MC) after allogeneic BMT in 35 consecutive patients with haematologic malignancies using a total CD4+ cell-depleted graft with an adjusted dose of CD8+ cells (1x10(8)/kg). Chimaerism was assessed by PCR amplification of VNTRs in 30 evaluable patients: 19 non-CML and 11 CML cases which were also evaluated for the BCR-ABL transcript by RT-PCR. All but one had complete engraftment with a donor profile early post-BMT. At the end of the study period, 12 of 30 patients displayed MC (40%). The overall disease-free survival for MC patients was clearly unfavourable when compared to those who exhibited a donor profile (24.7% vs. 100%, P = 0.005). However, we found that only two of five patients with MC in the non-CML group relapsed, whereas a clear correlation could be made between MC and relapse in CML (seven showed MC, preceding cytogenetic or haematological relapse in six of them, which displayed a prior BCR-ABL mRNA positivity). In addition, a quantitative-PCR approach enabled us to demonstrate that increasing amounts of MC are invariably associated with subsequent relapse, whereas a low stable level of host or complete donor haemopoiesis is consistent with clinical complete remission. Although these results suggest that the clinical impact of MC may depend on the underlying disease, it is compatible with the concept that the graft-versus-leukaemia effect against CML is mainly exerted by donor CD4+ lymphocytes. Elimination of this cellular subset may be responsible for the inability of the graft to prevent a progressive increase in the tumor cell burden.

[Right ventricle with double outlet associated to total anomalous pulmonary venous drainage to innominate vein]

The clinical findings of 2 patients are studied with an association of malformations not previously reported: double outlet right ventricle and total anomalous pulmonary venous connection to the innominate vein. The following features are worth while to be underlined: 1. Both patients showed a discordance between viscero-atrial situs and direction of the apex; 2. In both cases, particularly in case 2, there existed a very unusual spacial relationship between ventricles, the right ventricle being superior with respect to the left ventricular cavity; 3. From the embryological viewpoint, this ventricular arrangement is supposed to be due to an arrest of the development of the heart in the straight tube stage, there being, however, an upwards expansion of the atrioventricular canal and common atrium; 4. An accurate diagnosis of the common or divided nature of the atrioventricular valves has been impossible in these cases; 5. These combination of lesions constitutes a challenge to cardiologists and surgeons as far as the surgical indication is concerned. In that sense, the simple anastomosis of the common pulmonary vein to the left atrium, although is not a radical cure, may be a feasible and beneficial procedure.