Background: Respiratory tract infections (RTIs) represent a frequent cause of inpatient admission in children’s hospitals, especially in the fall and winter seasons, resulting in major healthcare problems due to a lack of beds. The age and seasonal distribution of each pathogen seem to be multifactorial features that influence the course of infection. Other severity predictors appear to be the length of hospital stay, the presence or absence of oxygen demand, and the value of inflammatory markers. Methods: All inpatients from our children’s hospital between 2021 and 2023 who had a nasopharyngeal swab and presented with RTI symptoms were recruited for this retrospective cohort study. The parameters of interest were age, swab result, month of detection, CRP values, duration of hospitalization, presence of oxygen demand, and comorbidities. The data were analyzed using chi-square tests, paired t-tests and regression analysis to determine the associations of differences between the groups. Results: Detection of more than one respiratory pathogen in the same swab, apart from combinations with SARA-CoV-2, influenza, or RS-virus, was not associated with longer hospital stay, higher mean maximal CRP values, or oxygen demand compared to mono-infection with the same pathogens. In contrast, the detection of a pathogen versus no detection could be related to higher rates of oxygen demand and higher CRP values. Conclusions: Since co-infection with more than one virus, excluding those with epidemic potential, was not associated with a more severe course of RTIs, strict patient isolation seems to be dispensable for several viruses, as well as isolation of infected or colonized patients.

Objectives: Detection and surveillance of SARS-CoV-2 is of eminent importance, particularly due to the rapid emergence of variants of concern (VOCs). In this study we evaluated if a commercially available quantitative real-time PCR (qRT-PCR) assay can identify SARS-CoV-2 B.1.1.7 lineage samples by a specific N gene dropout or Ct value shift compared with the S or RdRp gene. Methods: VOC B.1.1.7 and non-B.1.1.7 SARS-CoV-2-positive patient samples were identified via whole-genome sequencing and variant-specific PCR. Confirmed B.1.1.7 (n = 48) and non-B.1.1.7 samples (n = 58) were analysed using the Allplex (TM) SARS-CoV-2/FluA/FluB/RSV (TM) PCR assay for presence of SARSCoV-2 S, RdRp and N genes. The N gene coding sequence of SARS-CoV-2 with and without the D3L mutation (specific for B.1.1.7) was cloned into pCR (TM) II-TOPO (TM) vectors to validate polymorphism-dependent N gene dropout with the Allplex (TM) SARS-CoV-2/FluA/FluB/RSVTM PCR assay. Results: All studied B.1.1.7-positive patient samples showed significantly higher Ct values in qRT-PCR (06 - 10, N gene dropout on Ct values > 29) of N gene than the corresponding values of S (p <= 0.0001) and RdRp (p <= 0.0001) genes. The assay reliably discriminated B.1.1.7 and non-B.1.1.7 positive samples (area under the curve = 1) in a receiver operating characteristic curve analysis. Identical Ct value shifts (Delta 7 - 10) were detected in reverse genetic experiments, using isolated plasmids containing N gene coding sequences corresponding to D3 or 3L variants. Discussion: An N gene dropout or Ct value shift is shown for B.1.1.7-positive samples in the Allplex (TM) SARS-CoV-2/FluA/FluB/RSVTM PCR assay. This approach can be used as a rapid tool for B.1.1.7 detection in single assay high throughput diagnostics. (C) 2021 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

There is an urgent need for screening of patients with a communicable viral disease to cut infection chains. Recently, we demonstrated that ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is able to identify influenza-A infections in patients’ breath. With a decreasing influenza epidemic and upcoming SARS-CoV-2 infections we proceeded further and analyzed patients with suspected SARS-CoV-2 infections. In this study, the nasal breath of 75 patients (34 male, 41 female, aged 64.4 ± 15.4 years) was investigated by MCC-IMS for viral infections. Fourteen were positively diagnosed with influenza-A infection and sixteen with SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) of nasopharyngeal swabs. In one patient RT-PCR was highly suspicious of SARS-CoV-2 but initially inconclusive. The remaining 44 patients served as controls. Breath fingerprints for specific infections were assessed by a combination of cluster analysis and multivariate statistics. There were no significant differences in gender or age according to the groups. In the cross validation of the discriminant analysis 72 of the 74 clearly defined patients could be correctly classified to the respective group. Even the inconclusive patient could be mapped to the SARS-CoV-2 group by applying the discrimination functions. Conclusion: SARS-CoV-2 infection and influenza-A infection can be detected with the help of MCC-IMS in breath in this pilot study. As this method provides a fast non-invasive diagnosis it should be further developed in a larger cohort for screening of communicable viral diseases. A validation study is ongoing during the second wave of COVID-19. Trial registration: ClinicalTrial.gov, NCT04282135 Registered 20 February 2020—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04282135?term=IMS&draw=2&rank=1

Infectious pathogens are a global issue. Global air travel offers an easy and fast opportunity not only for people but also for infectious diseases to spread around the world within a few days. Also, large public events facilitate increasing infection numbers. Therefore, rapid on-site screening for infected people is urgently needed. Due to the small size and easy handling, ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is a very promising, sensitive method for the on-site identification of infectious pathogens based on scents, representing volatile organic compounds (VOCs). The purpose of this study was to prospectively assess whether identification of Influenza-A-infection based on VOCs by MCC-IMS is possible in breath. Nasal breath was investigated in 24 consecutive persons with and without Influenza-A-infection by MCC-IMS. In 14 Influenza-A-infected patients, infection was proven by PCR of nasopharyngeal swabs. Four healthy staff members and six patients with negative PCR result served as controls. For picking up relevant VOCs in MCC-IMS spectra, software based on cluster analysis followed by multivariate statistical analysis was applied. With only four VOCs canonical discriminant analysis was able to distinguish Influenza-A-infected patients from those not infected with 100% sensitivity and 100% specificity. This present proof-of-concept-study yields encouraging results showing a rapid diagnosis of viral infections in nasal breath within 5 min by MCC-IMS. The next step is to validate the results with a greater number of patients with Influenza-A-infection as well as other viral diseases, especially COVID-19. Registration number at ClinicalTrials.gov NCT04282135.

OBJECTIVES:Infections caused by vancomycin-resistant Enterococcus faecium (VREfm) represent a major public health concern due to limited treatment options. Among invasive isolates of VREfm, ST117, ST80 and ST78 represent the most frequently detected STs by MLST in Germany. In this study, we investigated the genetic diversity of isolates of VREfm recovered from different nosocomial outbreaks in Bavaria, Germany, by WGS.METHODS:Between January 2018 and April 2019, 99 non-replicate isolates of VREfm originating from nosocomial outbreaks at eight different hospitals in Bavaria were investigated for genetic diversity by WGS. In detail, complex types (CTs) were identified by core-genome MLST. Furthermore, an SNP analysis was performed for all VREfm strains.RESULTS:Most of the isolates of this study (76%) belonged to three major clonal groups, which occurred in at least three hospitals: ST80/CT1065 vanB (n = 45; six hospitals), ST117/CT71 vanB (n = 11; four hospitals) and ST78/CT894like vanA (n = 19; three hospitals). Moreover, isolates of the predominant lineage ST80/CT1065 vanB showed a maximum difference of 36 SNPs as revealed by SNP analysis.CONCLUSIONS:Whole-genome analysis of VREfm causing nosocomial outbreaks suggests the occurrence of few endemic clonal lineages in Bavarian hospital settings, namely ST80/CT1065 vanB, ST117/CT71 vanB and ST78/CT894like vanA. Further studies are needed for a better understanding of the factors affecting the successful spread of the above-mentioned lineages.

We documented and analyzed moth fly occurrence and spread of multidrug-resistant bacteria in a tertiary care hospital in Germany. The moth flies (Clogmia albipunctata) bred in the sewage system, then moved into the hospital, carrying biofilm and multidrug-resistant bacteria on their feet. Subsequently, the hospital developed a pest control protocol.

Regulatory T (Treg) cells induce immunologic tolerance by suppressing effector functions of conventional lymphocytes in the periphery. On the other hand, immune silencing is mediated by recognition of phosphatidylserine (PS) on apoptotic cells by phagocytes. Here we describe expression of the PS-binding protein Annexin V (ANXA5) in CD4+  CD25hi Treg cells at the mRNA and protein levels. CD4+  ANXA5+ T cells constitute about 0·1%-0·6% of peripheral blood CD3+ T cells, exhibit co-expression of several Treg markers, such as Forkhead box P3, programmed cell death protein-1, cytotoxic T-lymphocyte antigen-4 and CD38. In vitro, ANXA5+ Treg cells showed enhanced adhesion to PS+ endothelial cells. Stimulated by anti-CD3 and PS+ syngeneic antigen-presenting cells CD4+  ANXA5+ T cells expanded in the absence of exogenous interleukin-2. CD4+  ANXA5+ T cells suppressed CD4+  ANXA5- T-cell proliferation and mammalian target of rapamycin phosphorylation, partially dependent on cell contact. CD4+  ANXA5+ T-cell-mediated suppression was allo-specific and accompanied by an increased production of anti-inflammatory mediators. In vivo, using a model of delayed type hypersensitivity, murine CD4+  ANXA5+ T cells inhibited T helper type 1 responses. In conclusion, we report for the first time expression of ANXA5 on a subset of Treg cells that might bridge classical regulatory Treg function with immune silencing.

Introduction: Due to the increasing threat of resistant strains early diagnosis of pathogens is crucial for the therapy of infectious lung diseases. At last year9s meeting we could show the ability of multicapillary coupled ion mobility spectrometry (MCC-IMS) to rapidly distinguish different relevant bacteria in liquid culture and proposed also to investigate if multiresistant strains can be differentiated from susceptibles. Methods: Patient derived strains of E. coli (n=5), Haemophilus influenza (H. inf.; n=4), methicilline susceptible (MSSA; n=5) and resistant (MRSA; n=5) Staphylococcus aureus, Pseudomona aeruginosa (P. aer.; n=5), Proteus (n=5), Streptococcus pneumonia (Pneum; n=2), Klebsiella pneumonia (Klebs, n=5) and Klebsiella pneumonia expressing extended spectrum ß-lactamases (Klebs3; n=5) were diluted to MacFarland 0.5 and incubated in Brain Heart Infusion (Becton Dickinson). Non inoculated incubated tubes served as reference. After 90-110 min incubation at 37°C headspace was sampled and analyzed by MCC-IMS (STEP diagnostics, Pockau, Germany). The received spectra were analyzed by cluster analysis and 125 different clusters representing VOCs were derived. Results: By ROC analysis significant different VOCs could be found for all species even to distinguish between MRSA and MSSA and Klebs and Klebs3 respectively. Sensitivity (Sens) and specifity (Spec) were calculated for every used cluster using ROC analysis. Even between MSSA vs. MRSA and Klebs vs. Klebs3 with a Sensitivity of 100% and a specifity of 88% and 97% respectively. Conclusion: MCC-IMS is a promising tool for the detection of resistant strains in vitro. More resistant strains will be evaluated and presented.

Introduction: Early differentiation of bacterial species is crucial especially in the scope of emerging multiresistant strains. Conventional diagnosis takes about 3 working days even Maldi-TOF requires a preculture and is normally not available in less than 12 – 24 hours. During growth bacteria produce specific volatile compounds (VOC). At the 2014 ERS meeting we could show that these VOC can be detected 2 to 4 hours after incubation in headspace over solid culture but only 4 different bacteria species had been investigated. Methods and materials: In this study patient derived strains of E. coli (5), P. aeruginosa (5), H. influenza (4), Proteus mirabilis (5), MRSA (5), MSSA (5) and Streptococcus pneumoniae- (5) were diluted (McFarlane 0.5), incubated in Brain-Heart-Infusion liquid culture at 37° C for 90-120 minutes and measured as well as non inoculated specimens (7) by MCC-IMS (Fa. Graupner, Geyer). Results: 88 spectra could be derived by cluster analysis. For each species at least one cluster could be found that was significantly increased against all other species and controls. Using this single cluster specifity and sensitivity was calculated as well as for the combination of different clusters: Conclusion: By MCC-IMS a distinction of clinical important bacterial species is possible as early as 90-120 minutes after incubation even for MRSA and MSSA. Investigations with more species and strains are ongoing.

The transcription factor hypoxia inducible factor-1α (HIF-1α) mediates the metabolic adaptation of cells to hypoxia and T-helper cell fate. However, HIF-1α regulation in CD4 + T cells (T cells) remains elusive. Here we observed that depletion of oxygen (O 2 ⩽2%) alone was not sufficient to induce HIF-1α expression in T cells. However, when hypoxic T cells were stimulated, HIF-1α was expressed and this was dependent on nuclear factor-κB- and nuclear factor of activated T cell (NFAT)-mediated transcriptional upregulation of Hif-1α mRNA. HIF-1α upregulation could be blocked by drugs inhibiting NF-κB, NFAT or mammalian target of rapamycin precluding CD4 + T-cell stimulation or translation in T cells, as well as by blocking transcription. CD3, CD28, phorbol-12-myristat-13-acetat (PMA) or ionomycin-stimulated T cells did not express HIF-1α under normoxic conditions. In conclusion, regulation of HIF-1α expression in CD4 + T cells in hypoxia gravely relies on its transcriptional upregulation and subsequent enhanced protein stabilization.

The transcription factor hypoxia inducible factor‐1α (HIF‐1α) mediates the metabolic adaptation of cells to hypoxia and T‐helper cell fate. However, HIF‐1α regulation in CD4+ T cells (T cells) remains elusive. Here we observed that depletion of oxygen (O2⩽2%) alone was not sufficient to induce HIF‐1α expression in T cells. However, when hypoxic T cells were stimulated, HIF‐1α was expressed and this was dependent on nuclear factor‐κB‐ and nuclear factor of activated T cell (NFAT)‐mediated transcriptional upregulation of Hif‐1α mRNA. HIF‐1α upregulation could be blocked by drugs inhibiting NF‐κB, NFAT or mammalian target of rapamycin precluding CD4+ T‐cell stimulation or translation in T cells, as well as by blocking transcription. CD3, CD28, phorbol‐12‐myristat‐13‐acetat (PMA) or ionomycin‐stimulated T cells did not express HIF‐1α under normoxic conditions. In conclusion, regulation of HIF‐1α expression in CD4+ T cells in hypoxia gravely relies on its transcriptional upregulation and subsequent enhanced protein stabilization.

The central oxygen sensitive transcription factor HIF-1 has been implicated in the differentiation of nTreg and Th17 cells and to orchestrate metabolic changes of activated T cells. However, data on the functional relevance of HIF-1 and Hox, in general, for nTreg-suppressive activity and T cell function in primary human cells are still missing. Therefore, we analyzed the effect of Hox and HIF-1 on human Tres ,n Treg, and Th17 cells. Under Hox, nTregmediated suppression of Tres proliferation, CD25 expression, and secretion of IFN- were significantly reduced, whereas expression levels of VEGF, TNF-, and IL-10 were significantly increased. In contrast to observations in mice, Th17 lineage commitment, as determined by RORt expression, was not affected by activation or inhibition of HIF-1 expression using DMOG or YC-1 treatment, respectively. Nevertheless, the secretion of IL17A was increased by DMOG and reduced by YC-1 under Th17-skewing conditions in a dose- dependent manner. In conclusion, Hox and HIF-1 substantially influence human T cell-mediated immune responses by modulation of nTreg-suppressive function and IL-17A secretion by Th17 cells. J. Leukoc. Biol. 96: 000–000; 2014.

Most physiological processes in our body oscillate in a daily fashion. These include cerebral activity (sleep-wake cycles), metabolism and energy homeostasis, heart rate, blood pressure, body temperature, renal activity, and hormone as well as cytokine secretion. The daily rhythms in behaviour and physiology are not just acute responses to timing cues provided by the environment, but are driven by an endogenous circadian timing system. A central pacemaker in the suprachiasmatic nucleus (SCN), located in the ventral hypothalamus, coordinates all overt rhythms in our body through neuronal and humoral outputs. The SCN consists of two tiny clusters of ~100,000 neurones in humans, each harbouring a self-sustained, cell-autonomous molecular oscillator. Research conducted during the past years has shown, however, that virtually all of our thirty-five trillion body cells possess their own clocks and that these are indistinguishable from those operative in SCN neurones. Here we give an overview on the molecular and cellular architecture of the mammalian circadian timing system and provide some thoughts on its medical and social impact.

The central oxygen sensitive transcription factor HIF-1α has been implicated in the differentiation of n(T(reg)) and Th17 cells and to orchestrate metabolic changes of activated T cells. However, data on the functional relevance of HIF-1α and Hox, in general, for nT(reg)-suppressive activity and T cell function in primary human cells are still missing. Therefore, we analyzed the effect of Hox and HIF-1α on human T(res), n(Treg), and Th17 cells. Under Hox, nT(reg)-mediated suppression of T(res) proliferation, CD25 expression, and secretion of IFN-γ were significantly reduced, whereas expression levels of VEGF, TNF-α, and IL-10 were significantly increased. In contrast to observations in mice, Th17 lineage commitment, as determined by RORγt expression, was not affected by activation or inhibition of HIF-1α expression using DMOG or YC-1 treatment, respectively. Nevertheless, the secretion of IL-17A was increased by DMOG and reduced by YC-1 under Th17-skewing conditions in a dose- dependent manner. In conclusion, Hox and HIF-1α substantially influence human T cell-mediated immune responses by modulation of nT(reg)-suppressive function and IL-17A secretion by Th17 cells.

Regulatory CD8(+) T cells are critical for self-tolerance and restricting excessive immune responses. The variety of immune functions they fulfill, the heterogeneity of their phenotype, and the mechanism of action are still poorly understood. Here we describe that regulatory CD8(+) T cells exhibiting immunosuppressive actions in vitro and in vivo are recognized as CD38(high) T cells and present in naive mice. CD38 is a glycosylated membrane protein with ectonucleotidase properties. CD8(+)CD38(high) (CD44(+)CD122(+)CD62L(high)) lymphocytes suppress CD4(+) effector T-cell proliferation in an antigen-non specific manner via IFN-γ. While direct cell-to-cell contact is needed for this suppressor activity, it is independent of membrane-bound TGF-β and granzyme B release. IL-15 potentiates the suppressive activity of CD8(+)CD38(high) T cells and controls their survival and expansion. In humans CD8(+)CD38(high) T cells inhibit CD4(+) effector T cell proliferation. In vivo, CD8(+)CD38(high), but not CD8(+)CD38(-) T cells mitigate murine experimental autoimmune encephalomyelitis (EAE) by reducing the clinical score and delaying disease occurrence. EAE suppression is enhanced by pre-treatment of CD8(+)CD38(high) T cells with IL-15. These findings add evidence that the expression of ectoenzyme receptor family members positively correlates with suppressor functions and identifies CD8(+)CD38(high) T cells as potential inhibitors of excessive immune responses.

Though it has been shown that immunological functions of CD4+ T cells are time of day-dependent, the underlying molecular mechanisms remain largely obscure. To address the question whether T cells themselves harbor a functional clock driving circadian rhythms of immune function, we analyzed clock gene expression by qPCR in unstimulated CD4+ T cells and immune responses of PMA/ionomycin stimulated CD4+ T cells by FACS analysis purified from blood of healthy subjects at different time points throughout the day. Molecular clock as well as immune function was further analyzed in unstimulated T cells which were cultured in serum-free medium with circadian clock reporter systems. We found robust rhythms of clock gene expression as well as, after stimulation, IL-2, IL-4, IFN-γ production and CD40L expression in freshly isolated CD4+ T cells. Further analysis of IFN-γ and CD40L in cultivated T cells revealed that these parameters remain rhythmic in vitro. Moreover, circadian luciferase reporter activity in CD4+ T cells and in thymic sections from PER2::LUCIFERASE reporter mice suggest that endogenous T cell clock rhythms are self-sustained under constant culture conditions. Microarray analysis of stimulated CD4+ T cell cultures revealed regulation of the NF-κB pathway as a candidate mechanism mediating circadian immune responses. Collectively, these data demonstrate for the first time that CD4+ T cell responses are regulated by an intrinsic cellular circadian oscillator capable of driving rhythmic CD4+ T cell immune responses.

Sleep regulates immune functions. We asked whether sleep can influence immunological memory formation. Twenty-seven healthy men were vaccinated against hepatitis A three times, at weeks 0, 8, and 16 with conditions of sleep versus wakefulness in the following night. Sleep was recorded polysomnographically, and hormone levels were assessed throughout the night. Vaccination-induced Th cell and Ab responses were repeatedly monitored for 1 y. Compared with the wake condition, sleep after vaccination doubled the frequency of Ag-specific Th cells and increased the fraction of Th1 cytokine-producing cells in this population. Moreover, sleep markedly increased Ag-specific IgG1. The effects were followed up for 1 y and were associated with high sleep slow-wave activity during the postvaccination night as well as with accompanying levels of immunoregulatory hormones (i.e., increased growth hormone and prolactin but decreased cortisol release). Our findings provide novel evidence that sleep promotes human Th1 immune responses, implicating a critical role for slow-wave sleep in this process. The proinflammatory milieu induced during this sleep stage apparently acts as adjuvant that facilitates the transfer of antigenic information from APCs to Ag-specific Th cells. Like the nervous system, the immune system takes advantage of the offline conditions during sleep to foster adaptive immune responses resulting in improved immunological memory.

Dharam V. Ablashi Robert Ader Javed Agrewala Armin Alaedini Jessy J. Alexander Nabil Alkayed Stuart Allan Francesca Aloisi David Amaral Barbara Andersen Monica Andersen Hymie Anisman Djillali Annane Daniel Anthony Alexios Antonopoulos Hiroyuki Arakawa Paul Ashwood Djordje Atanackovic Arnaud Aubert Marie-Claude Audet Stéphane Auvin Ronit Avitsur Yosefa Avraham Matthew Bailey Michael Bailey William A. Banks Mary Barbe R. A. Barker Ruth Barrientos A. Bartolomucci Sujit Basu Moisés Bauer Karl Bechter K. Beck Jonathan Beever Denise L. Bellinger Christian Benedict Shamgar Ben-Eliyahu Sven Benson Istvan Berczi Martha Bernardi John Bethea David Beversdorf Cordian Beyer John Bienenstock Staci Bilbo Bonnie Blomberg Anders Blomqvist Gary Boehm Thomas Bollinger Christopher Bolton Robert H. Bonneau Roger John Booth Jan Born Francesca Bosetti Oscar Bottasso L. M. Boulanger Julienne E. Bower Adrian Bradley Darrell Brann Gordon Broderick Jessica Buchanan Lionel Bueno Nicole Bush Angelika Buske-Klrschbaum Joao Calixto John Campbell John P. Capitanio Lucile Capuron Amber Cardani Astrid Cardona Nicoletta Carlo-Stella Eugenio Carrasco-Marin Jude Carroll Monica J. Carson Bruce Carter Chris Carter Livia Carvalho Nathalie Castanon Maria Castro Diego Centonze Sulie Chang Edith Chen P. D. Cheney Lisa Christian George Chrousos Christopher Coe Frances Cohen J. A. Cohen Steve Cole Mark Connor Thomas Connor Bruno Conti Marcus Cooke Mary Coussons-Read Jacqueline Crawley J. David Creswell Changhai Cui Libin Cui Colm Cunningham Claudio D’Addario S. Dane Andrea Danese R. Dantzer U.N. Das Tye Dawood A. L. De Oliveira Terrence Deak Adriana Del Rey Adam Denes Noel Derecki Michael Dettling Courtney DeVries Firdaus Dhabhar Sally S. Dickerson Dara Dickstein Stoyan Dimitrov Joel Dimsdale Timothy Dinan Bonnie Dittel Denise Dixon Steven D. Douglas Jennifer Dowd Hemmo Drexhage Ronald Duman Adrian J. Dunn Naomi Eisenberger Christopher Engeland Harald Engler Mary-Anne Enoch Elissa Epel Michael Esser Dwight Evans Zsuzsanna Fabry Eduardo Fano C. Farmer Hossein S. Fatemi Joram Feldon Rafael Fernandez-Botran M. Fernandez-Cabezudo Laurent Ferrier Serguei Fetissov N. Filipov Monika Fleshner Terry Flotte Matthew Frank Frances Frankenburg Dan Frenkel Gregory Freund Elliot Friedman Robert Fujinami Vilma Gabbay Sandro Galea Norma Galindo-Sevilla Doina Ganea Hui-Ming Gao Luis Garcia-Segura Laurent Gautron Ronald Gaykema Dori Germolec Jessica Gill Ronald Glaser Mike Gleeson Jonathan Godbout Lisa Goehler Reginald M. Gorczynski Liam Gray Jeffrey Greeson Pierre Gressens James Griffith Elena Grigorenko Angela Grippo Maureen Groer Tara Gruenewald C. Guaza Paolo Gubellini Vinod Gupta Uwe-Karsten Hanisch Helene Hardin-Pouzet Andrew Harkin Gaylia Harry S. Hayley Kathi Heffner Cobi Heijnen Amy Hein J. Henkel Michael Hennessy Peter Henningsen Miles Herkenham Gretchen Hermes Robin Hilsabeck Deborah M. Hodgson Jacob Hollis Suzi Hong Wenhui Hu Inge Huitinga Brain, Behavior, and Immunity 25 (2011) 178–180