Mosquitoes transmit hundreds of arboviruses. The ability to estimate the titers of viruses transmitted from infectious mosquitoes to a host is critical. In this study, we evaluated forced salivation techniques to estimate and compare titers of Zika virus and chikungunya virus transmitted by the mosquitoes. We demonstrated that performing forced salivation on mosquitoes after blood feeding might be an efficient way to estimate the virus transmitted during blood feeding. Additionally, by comparing titers of bloodmeals and saliva post-feeding, we showed that mosquitoes re-ingest much of their saliva during artificial blood feeding. The results from this study add new information to understanding and quantifying the transmission of arboviruses.Aedes aegypti. Infectious virus and viral genomes of both viruses were detected more often from individual mosquitoes using immersion oil for the FS media compared to fetal bovine serum (FBS) plus glycerol, but the FS media had no influence on virus quantification from positive samples. FS virus titers were equivalent when comparing individuals or groups of mosquitoes that never received a blood meal compared to those that were blood fed immediately prior, showing that blood feeding does not influence FS. This suggested that performing FS on mosquitoes after blood feeding might be an efficient way to estimate virus transmitted during blood feeding. However, detecting virus from the blood remaining in an artificial feeder post-blood feeding was mostly unsuccessful relative to quantifying virus from FS of the post-blood fed mosquitoes. In contrast, immunocompromised mice always became infected after being fed on by Zika-infected mosquitoes, even when no infectious virus was detected in their saliva by FS post-blood feed. Due to this discrepancy, we tested the ingested bloodmeals of individual mosquitoes that fed on artificial blood feeders for virus, and compared these to virus in their saliva harvested from FS and to virus in their bodies. These experiments revealed ~50–100 times higher virus titers in the dissected bloodmeals compared to those detected in the same mosquitoes’ saliva, demonstrating how mosquitoes re-ingest much of their saliva during artificial blood feeding, and highlighting a large increase in virus transmission during Aedes aegypti blood feeding. Both FS and the dissected bloodmeals of artificially blood-fed mosquitoes showed that the quantity of viral RNA expectorated by mosquitoes was 2–5 logs more than the quantity of infectious virus. The results from this study add critical information to understanding and quantifying the transmission of Aedes aegypti arboviruses.Arbovirus transmission studies are dependent on the ability to estimate the titer of virus transmitted from infectious mosquitoes to a host. There are several methods for estimating virus titer in mosquito saliva, including (1) using forced salivation (FS) whereby the infectious mosquito’s proboscis is forced into a capillary tube containing media to collect and test their saliva for virus, and (2) by quantifying virus expectorated into host tissues or into the blood contained in an artificial feeder immediately after blood feeding. We studied FS and bloodmeals to estimate and compare titers of Zika virus and chikungunya virus transmitted by the mosquito vector  Estimating the titer of arboviruses transmitted by mosquitoes during blood feeding on a host is critical to understand arbovirus transmission, especially by accurately simulating these natural infections in laboratory studies. There are several documented methods for collecting saliva and/or determining the efficiency and titer of virus transmitted from mosquito saliva to a host: 1) forced salivation (FS) of infectious mosquitoes into media contained in a capillary tube and testing the captured saliva for virus, 2) detecting virus in host tissues immediately after infectious mosquitoes blood feed or by later examining host infection or seroconversion rates, and 3) detecting virus in the remaining blood from artificial feeders fed upon by infectious mosquitoes [ forced s detectin detectinAedes albopictus infected with Venezuelan equine encephalitis virus (VEEV) showed that there was no difference between virus titers when saliva was collected in either immersion oil or FBS using the FS technique [Forced salivation is often used as it can determine virus expectorated from a single mosquito and is not dependent on the mosquito blood feeding. Within this method, different media have been used within the capillary tube, the most common being either microscope immersion oil ,4 or fetAedes aegypti used mouse intracerebral 50% lethal doses to show that the amount of virus transmitted varied from being undetectable to 1.0 × 105 [3 PFU as measured by FS collections with immersion oil [Culex tarsalis after blood feeding determined that virus transmitted was approximately 600-fold higher than virus transmitted during the FS technique [Culex pipiens quinquefasciatus by blood feeding and forced salivation [In addition to forced salivation, vertebrate hosts or artificial feeders can be used to estimate the amount of virus being transmitted from an infectious mosquito bite. However, mosquito feeding behaviors are inconsistent, especially in high-containment (BSL-3) laboratory settings because of rapid air exchange and personal protective equipment that limit body heat and odor cues, so there is no way to ensure any one mosquito, or recalcitrant species or strains, will take a blood meal . A study.0 × 105 . An addision oil . Compariechnique , but anolivation . Taken tAedes aegypti mosquitoes infected with Zika virus (ZIKV) and chikungunya virus (CHIKV). Our efforts examined variations on the FS technique and compared it to virus transmission during blood feeding on animals and artificial feeders, and also to re-ingested virus recovered from bloodmeals dissected out of the mosquitoes , originally isolated from a human traveler to Puerto Rico in 2015 with three rounds of amplification on Vero cells, was obtained from Dr. Aaron Brault . CHIIKV strain LR2006_OPY1 (GenBank: KT449801.1) was obtained from the University Texas Medical Branch and isolated from outbreak in Reunion Island in 2006 with three rounds of amplification on Vero cells.African Green Monkey kidney cells  were maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum , 2 mM L-glutamine (Gibco Thermo Fisher), 1.5 g/L sodium bicarbonate (Gibco Thermo Fisher), 100 U/mL penicillin (Gibco Thermo Fisher) and incubated at 37 °C in 5% COAedes aegypti Poza Rica strain mosquitoes were fed an infectious artificial blood meal containing either CHIKV or ZIKV and held for 10–14 days before all subsequent experiments to ensure dissemination of virus to the salivary glands. Infectious bloodmeals were prepared with 1 mL fresh virus contained in the cell-culture supernatant of infected Vero cells and 1 mL of defibrinated calf blood. Back-titering of the bloodmeals ranged between 1 × 106–5 × 106 PFU/mL. Mosquitoes were sorted post blood feeding and were placed in cartons  with an organdy cover and given water and a sugar source.Aedes aegypti Poza Rica strain mosquitoes were fed an infectious blood meal and held for 14–17 days. Mosquitoes were sorted post blood feeding and 10–20 blood-fed mosquitoes were place in cartons with an organdy cover and given water and a sugar source. To allow the mosquitos to feed on the mice, each mouse was anesthetized using 100 mg/kg ketamine/10 mg/kg xylazine  and placed on the organdy cover of one carton for ~20 min.A129 mice  8–12 weeks old were obtained from breeding colony maintained at Colorado State University. Use of mice was approved by the Colorado State University Institutional Animal Care and Use Committee (protocol 15-6677 AA). All procedures were done in accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. To infect mice by mosquito bite, Mosquitoes were immediately cold-anesthetized post-blood feeding and their saliva was collected by the FS method described previously , brieflyBloodmeal dissections were done immediately after individual mosquitoes underwent FS. Mosquitoes were dissected on the sides of glass wells partially filled with 200 µL of DMEM supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 1.5 g/L sodium bicarbonate, 100 U/mL penicillin. The midguts were dissected out and spilt open so that the blood meal contents could spill out into the media, and the torn midgut swished into media to extract the whole blood meal. Mock blood meal dissections were performed on non-blood fed mosquitoes exactly the same way but there was no blood meal that could spill out into the media. The media  was then collected and placed into a tube for later testing, and the body plus torn midgut were placed into another tube and frozen at −80 °C to be homogenized in media for later testing.g. Bloodmeals were collected in 150 µL of DMEM supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 1.5 g/L sodium bicarbonate, 100 U/mL penicillin. RNA was extracted from all samples using the Mag-Bind Viral DNA/RNA 96 kit (Omega Bio-Tek) on the KingFisher Flex Magnetic Particle Processor (Thermo Fisher Scientific). RNA was eluted in 30 µL nuclease-free water. Progmeg GoTaq Probe 1-Step RT-qPCR System Kits were used on RNA extracted from saliva and bodies to quantify CHIKV and ZIKV RNA according to manufacturers’ instructions. Standard cycling condition were followed, one cycle at 45 °C for 15 min, one cycle at 95 °C for 2 min and 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Primers used for CHIKV were Forward (5′-CTTTGAAGTTTCCTTTCGGTGG-3′) and Reverse (5′-ACFFAAFFRAAACTGGTATGG-3′) and Probe-FAM (5′-TCTGCAGCGTCTTTATCCACGGG-3′). Primers used were ZIKV 1086 (5′-CCGCTGCCCAACACAAG-3′) and ZIKV 1162c (5′-CCACTAACGTTCTTTTGCAGACAT-3′). The probe used was ZIKV 1107-FAM (5′-AGCCTACCTTGACAAGCAGTCAGACACTCAA-3′) [2 value of 0.971 to 0.997, a slope of −3629 to −3269, and y-intercept = 37.966 to 47.270.Tubes containing mosquito bodies were homogenized and both saliva and bodies where centrifuged for 5 min at 14,000× t-test or a one-way analysis of variance (ANOVA) with a Tukey’s multiple-comparison in GraphPad Prism. Correlation was determined by Spearman’s rank-order correlation in the GraphPad Prism , La Jolla, CA, USA).Results in figures were expressed as mean values  with individual values showing the variance. The statistical details are noted in the figures and/or in the corresponding figure legends. Statistical significance was primarily determined using either Fisher’s exact test, unpaired Student’s Aedes aegypti were subjected to FS using two different media, there was a significant difference in the proportion of positive saliva samples from mosquitoes that salivated into oil compared to FBS + glycerol regardless of virus (p ≤ 0.05). The same pattern was seen with detection of infectious CHIKV, with 38% (38/100) of positive saliva samples collected in oil compared to 14% (14/100) from FBS + glycerol (p ≤ 0.05). When testing for viral RNA in the same samples, the same pattern was observed, with oil resulting in more positive samples than the FBS + glycerol media for both viruses. However, viral RNA was detected in more samples overall than infectious virus for both viruses. Despite the increased virus prevalence in saliva samples collected using oil, positive samples from both FS media did not significantly differ in the quantity of infectious virus or viral RNA for either virus Comparisons of virus titers transmitted by ZIKV- and CHIKV-infected  fed see . There w fed see . Overall2–6.8 × 104 genome copies) via FS  from Ae. aegypti. Considering that quantification of viral RNAs from FS of both groups of blood fed mosquitoes was roughly equal, the combined data suggested that some factor was inhibiting our ability to detect arbovirus transmission by Ae. aegypti from the blood in the artificial feeders. We hypothesized that this inhibitory factor was mosquito re-ingestion of their saliva, and thus the virus they expectorated, during blood feeding on artificial feeders.Overall, 53 immunocompromised mice were fed upon by groups of ZIKV-infected mosquitoes  and all became infected with ZIKV. ) via FS . In cont) via FS . These dp ≤ 0.05). A similar difference was seen with CHIKV-infected mosquitoes (none = 2.067 PFU/5.195 genome copies (gc), artificial feeder = 3.443 PFU/6.832 gc, artificial feeder + mixing = 3.739 PFU/6.659 gc) (p ≤ 0.05).To test our hypothesis of re-ingested virus during blood feeding, we dissected and tested the bloodmeals of ZIKV- and CHIKV-infected mosquitoes after they fed on artificial feeders and then underwent forced salivation. As the process of dissecting out the blood meal results in some contamination of virus into the dissecting media from the hemolymph and midgut tissue of these infected mosquitoes, mock blood meal dissections were performed as treatment controls on groups of mosquitoes that did not get a second bloodmeal. Approximately 100-fold more infectious ZIKV or ZIKV RNA, as well as infectious CHIKV or CHIKV RNA, was detected in the bloodmeals from individual mosquitoes relative to the treatment controls . These rAedes aegypti mosquitoes after being infected with either ZIKV or CHIKV. Different medias have been previously evaluated for FS, including immersion oil and a mixture of 1:1 FBS + glycerol, as well as blood and other medias [Ae. aegypti infected with CHIKV or ZIKV. We found no evidence that FBS + glycerol aided in viral stabilization and preservation as was previously suggested [Aedes aegypti expectorated a mean of 6.8 nL using oil-based FS and observed no correlation of CHIKV titers with the saliva volume expectorated. Another potential benefit of oil-based FS is that the mosquitoes are unable to re-ingest their own saliva. It has been previously shown that anopheline mosquitoes will re-ingest many of the Plasmodium sporozoites they deposit in the host when blood feeding [We used different experimental procedures and methods to estimate the titer of virus transmitted by r medias ,17,18,19uggested ,9 and nouggested . In the  feeding . It follFS has been used as the standard method to determine transmission of mosquito-borne arboviruses ,2,4,5, bTo compare our post-blood feeding FS data with the quantity of virus transmitted during the blood feed, we analyzed outcomes of ZIKV-infected mosquitoes that blood fed on immunocompromised mice, and virus transmitted to artificial feeders after ZIKV- or CHIKV-infected mosquitoes fed on them. Mice became infected after mosquito feeding even when no infectious virus was detected in the mosquito saliva post feeding. Our limit of detection is 2 PFU and 10 genomes copies; however, we never detected anything under 10 PFU. Based on these results, we can assume these mice can become infected with less than 10 PFU transmitted by mosquitoes blood feeding on them. When examining the blood remaining in the artificial feeders, however, infectious virus was never recovered, and viral RNA was only recovered in four out of nine ZIKV groups and one out of nine CHIKV groups. This observation could be explained in at least two non-exclusive hypotheses. It may be that live virus was quickly inactivated and viral nucleic acid sequences were destroyed by proteases and nucleases in the artificial blood meal, making their detection difficult by plaque assay and qRT-PCR, respectively. However, this seems unlikely given that we rarely record a drop in virus titer of the original blood meal used to first infect the mosquitoes when it is ‘back-titered’ after sitting in the artificial feeder for ~30 min during the blood feed. Another possibility is that virus expelled with the saliva into the artificial blood meal may be immediately re-ingested through the suction force needed to bring blood into the food canal.Ae. aegypti transmitting either ZIKV or CHIKV and between quantities of infectious virus or viral RNA detected; between 50–100 times more virus is secreted during blood feeding than is detected in FS performed immediately after blood feeding, suggesting a large increase in virus transmission during blood feeding. One limitation of these data are that they are estimates of virus transmission by Ae. aegypti derived from blood feeding on artificial feeders, which may not accurately reflect what occurs during blood feeding on live hosts, including transmission during probing but not blood feeding [2–2.1 × 1010 when the mouse ear tissue was immediately removed and homogenized after being fed on by ZIKV-infected Ae. aegypti mosquitoes [To address the latter hypothesis, we dissected out bloodmeals from the infected mosquito midguts after they were given different blood feeding treatments and then were processed with FS. For one of the blood feeding treatments, blood was pipetted up and down in the blood feeder during the time of feeding to determine if blood mixing might counteract the re-ingestion of a mosquito’s own expectorated virus during blood feeding. Compared to the control treatment , significantly more virus and viral RNA was recovered from the bloodmeals of the two blood feeding treatment groups, and the mixing of the blood in the artificial feeder did not influence this. This indicated that mosquitoes re-ingest much of their expectorated virus while feeding on the artificial feeder and that poor detection of virus in the remaining blood from artificial feeding is likely due to re-ingestion. As each mosquito dissected of its bloodmeal was also processed via FS, we could determine the difference of virus titers between the bloodmeal and saliva to estimate the quantity of virus transmitted during blood feeding. The estimate was consistent between  feeding . However feeding . Each ofsquitoes . In our Ae. aegypti mosquito by performing FS on it immediately post-blooding, quantifying infectious virus or viral RNA and then multiplying the titer determined by ~50–100. Quantifying infectious virus ensures measurement of true infectious units, but it is clearly of low sensitivity and so simultaneously quantifying viral RNA will give the best estimates of transmission dose. More experiments will be necessary to determine if the increase in virus transmission during blood feeding relative to FS we observed is because of (a) more saliva being released by Ae. aegypti or (b) more virus being released from the salivary glands, or both. Similarly, results from this study should be replicated with other arbovirus vectors to determine if they are consistent across mosquito species. Overall, the methods developed here can be used as a better way to estimate the titer of arboviruses transmitted by blood feeding Ae. aegypti and may be valuable for similar estimations with other mosquitoes.Studies using different combination of viruses and mosquito species have evaluated the use of vertebrate hosts or artificial feeders to estimate the amount of virus being transmitted from an infectious mosquito and found varying results ,12,13,14


Ureaplasma respiratory colonization who participated in a double-blind, placebo-controlled randomized controlled trial.To assess the potential impact of azithromycin treatment in the first week following birth on 2-year outcomes in preterm infants with and without Respiratory morbidity was assessed at NICU discharge and at 6, 12, and 22–26 months corrected age using pulmonary questionnaires. Comprehensive neurodevelopmental assessments were completed between 22 and 26 months corrected age. The primary and secondary composite outcomes were death or severe respiratory morbidity and death or moderate–severe neurodevelopmental impairment, respectively, at 22–26 months corrected age.N = 60; placebo, N = 61) were included in the intent-to-treat analysis. There were no significant differences in death or serious respiratory morbidity  or death or moderate–severe neurodevelopmental impairment  between the azithromycin and placebo groups. Among all trial participants, tracheal aspirate Ureaplasma-positive infants experienced a higher frequency of death or serious respiratory morbidity at 22–26 months corrected age (58%) than tracheal aspirate Ureaplasma-negative infants (34%) or non-intubated infants (21%) (p = 0.028).One hundred and twenty-one randomized participants (azithromycin, We did not observe strong evidence of a difference in long-term pulmonary and neurodevelopment outcomes in preterm infants treated with azithromycin in the first week of life compared to placebo.No strong evidence of a difference in long-term pulmonary and neurodevelopment outcomes was identified at 22–26 months corrected age in infants treated with azithromycin in the first week of life compared to placebo.The RCT is the first study of 2-year pulmonary and neurodevelopmental outcomes of azithromycin treatment in ELGANs.Ureaplasma have the most frequent serious respiratory morbidity in the first 2 years of life, suggesting that a Phase III trial of azithromycin to prevent BPD targeting this population is warranted.Provides evidence that ELGANs with lower respiratory tract  To determine the long-term safety of neonatal AZM therapy and the potential impact on long-term outcomes, pulmonary and neurodevelopmental outcomes were assessed at 22–26 months corrected age in participants of the randomized controlled trial (RCT).We conducted a series of pharmacokinetic/pharmacodynamic open-label studies of intravenous azithromycin (AZM)21 The sample size for the trial was calculated to provide good power to detect moderate differences in the primary outcome of Ureaplasma-free survival to discharge. The U.S. Food and Drug Administration (IND78990) and the Institutional Review Board of each participating institution approved the study protocol including follow-up. Written parental consent was obtained for all participants prior to randomization. One hundred and twenty-one ELGAN infants  were enrolled and randomized at 7 U.S. centers between July 2013 and August 2016.21 After baseline respiratory samples were obtained, participants were randomized to receive either intravenous AZM  20 mg/kg at a concentration of 2 mg/ml in 5% dextrose water or equal volume of 5% dextrose water (10 ml/kg) as a placebo administered every 24 h for 3 doses. Randomization was performed using permuted block design with stratification by site and gestational age (240–266 vs 270–286 weeks) and assigned in 1:1 ratio to AZM or placebo with twins assigned to the same treatment. Since rapid diagnostic testing for Ureaplasma spp. was not feasible, presence of Ureaplasma colonization was unknown prior to dosing. All tracheal and nasopharyngeal aspirate samples were frozen at −80 °C at each study site and batch-shipped to the University of Alabama at Birmingham Diagnostic Mycoplasma Laboratory for Ureaplasma culture, species-specific real-time PCR and AZM susceptibility testing. Ureaplasma eradication was defined as three negative cultures post-treatment.21The study design was a prospective, randomized, double-blind, placebo-controlled trial  as recently described.21 BPD was classified as physiologic based on a room air challenge,22 modified Shennan based on supplemental oxygen use at 36 weeks PMA or time of transfer prior to 36 weeks PMA,23 and NIH BPD severity definitions.24 Socioeconomic factors, including insurance status, maternal education and marital status, and primary language spoken at home were collected at the 22–26-month corrected age visit. For all neonatal intensive care unit (NICU) and follow-up assessments, the examiners were masked to treatment assignment and Ureaplasma colonization status. Only the pharmacists at each site were unblinded to treatment assignment.Data collected at baseline and during hospitalization included demographic variables such as gestational age, birth weight, sex, race, and ethnicity, and neonatal morbidities, including IVH grade, periventricular leukomalacia, necrotizing enterocolitis stage, late-onset sepsis, patent ductus arteriosus, retinopathy of prematurity stage, and postnatal steroid use, tracheostomy placement, postmenstrual age (PMA) at the time of discharge to home, and modes and duration of respiratory support.27 Follow-up interview windows were 5–9 months corrected age with an ideal interview date at 6 months corrected age, 10–18 months with an ideal interview date at 12 months, and 19–30 months with the ideal date at 24 months corrected age. At the time of each parental interview, the parent/caregiver was asked to provide responses based on the interval since the last interview. Information was elicited on family history of asthma and atopy, the home environment such as presence of pets and tobacco smoke exposure, the frequency and characteristics of wheezing and cough, use of respiratory medications including diuretics, nebulized bronchodilators, inhaled or systemic steroids, supplemental oxygen, and respiratory illness-related hospitalizations, physician visits, or emergency room (ER) visits. Parental report of their child experiencing cough without a cold “most of the time” during an interval was classified as chronic cough and parental report of wheezing “almost every day” during an interval was classified as chronic wheezing.Structured parental interviews were conducted before discharge and by follow-up phone interviews at 6, 12, and 22–26 months corrected age using the validated Tucson Children’s Respiratory Study questionnaires.28 that included a standardized assessment of reflexes, muscle tone, and strength were classified as normal, suspect , abnormal with functional impairment due to noncerebral palsy, or abnormal due to cerebral palsy (CP). Gross motor performance was evaluated using the modified Gross Motor Function Classification System (GMFCS) with scores ranging from 0  to 5 (most impaired).29 CP severity was classified as mild (GMFCS level 1), moderate (GMFSC levels 2–3), or severe (GMFCS levels 4–5).30 Certified examiners assessed cognitive function using the Bayley Scales of Infant and Toddler Development, third edition (BSID-III).31 For participants whose parents were unable to bring them to the clinic for in-person assessments, a parental phone interview was conducted to complete the Ages and Stages Questionnaire, Third Edition (ASQ3) to score developmental milestones in five domains .32 Hearing impairment  were assessed by observation, parental report, or follow-up audiologic assessments.33 Vision impairment defined as vision worse than 20/200 was obtained by parental report or post-discharge eye exams. If unable to complete either in-person assessments or the phone interview ASQ3, information was extracted from chart review to classify the child for neurodevelopmental impairment (NDI).Surviving infants completed comprehensive neurodevelopmental assessments between 22 and 26 months corrected age. Neurologic examinations34 The secondary outcome was the composite outcome of death prior to 26 months corrected age or moderate-to-severe NDI at 22–26 months corrected age defined as any one of the following: BSID-III cognitive composite score <85 or ASQ score >2 SD below the mean on any domain,32 GMFCS score ≥2, moderate or severe CP, blindness, and/or severe hearing impairment that cannot be corrected by amplification.30 Other secondary outcomes included mortality, the components of the pulmonary and neurodevelopmental composite outcomes, parental report of chronic wheezing or cough, doctor/ER visits for respiratory illness, and respiratory medication use during the first 22–26 months corrected age.The primary outcome for the follow-up phase of the trial was the composite outcome of death prior to 26 months corrected age or serious respiratory morbidity, defined as the occurrence of one or more of the following: tracheostomy; continued hospitalization for respiratory reasons at or beyond 50 weeks PMA, use of supplemental oxygen or respiratory support at 22–26 months corrected age, or ≥2 rehospitalizations for respiratory illness.Ureaplasma-positive and negative participants. To account for possible correlation between outcomes in twins, we used generalized estimating equations35 and multiple outputation to calculate p values and confidence intervals.36 When observed counts were small, we used exact methods without accounting for twinning to calculate p values.For the efficacy analysis, we compared the composite outcome death or serious respiratory morbidity at 22–26 months corrected age and other outcomes among all randomized participants according to the principle of intention-to-treat and in the subgroups of 37We did not collect a 22–26 month lung assessment for 15 of the children. To retain these children in the analyses described above, we multiply imputed the outcomes based on information gathered in the 6- and 12-month follow-up surveys and on respiratory variables observed prior to discharge. Binary outcomes were imputed based on their estimated probability. Twenty-five data sets with imputations were created and the final results were combined using Rubins approach.Treatment groups were compared with respect to the median value of several quantitative outcomes, including PMA at discharge to home and when supplemental oxygen was discontinued. To include children who died during the NICU hospitalization in the analysis appropriately, we used a rank-based (Wilcoxon test) analysis and gave these children the worst ranks.Ureaplasma colonization on the follow-up primary and major secondary outcomes.In post hoc analyses, we explored the impact of upper and lower respiratory tract All analyses were performed using SAS 9.4.21 One placebo-assigned infant who was nasopharyngeal Ureaplasma positive received a single dose of AZM due to pharmacy error. The baseline characteristics of the study cohort and when stratified by Ureaplasma colonization status were similar between treatment arms, except for an imbalance in race distribution that occurred with 40% non-white in the AZM vs 75% in the placebo group  received at least one dose of the assigned treatment  and 1 AZM-assigned participant died after discharge and prior to 22–26-month corrected age. At least one post-discharge questionnaire was completed for 105/109 survivors (96%). At 22–26 months corrected age, 94 (86%) completed pulmonary assessments and 95 (87%) completed neurodevelopmental assessments  but significantly higher incidence of serious respiratory morbidity than placebo-assigned participants (45 vs 15%) , with nebulized albuterol as the most frequent medication used in both the groups. There were no appreciable differences in percentage of children who were hospitalized one or more times for respiratory illness between treatment arms and when stratified by Ureaplasma status.The primary composite pulmonary outcome of death prior to 22–26 months corrected age or serious respiratory morbidity was similar in the AZM (34.8%) compared to the placebo (30.4%) group . There were no significant differences in composite outcome of death or moderate–severe NDI when stratified by Ureaplasma respiratory colonization status (Table p = 0.024)  survivors  and mortality from respiratory causes  was greater in the Ureaplasma-positive group than for infants assigned to placebo. In patients with lower respiratory tract Ureaplasma colonization, death or serious respiratory morbidity was 60% (6/10) in AZM-treated vs 56% (6/11) in placebo-treated infants , our data do not rule out either a moderately reduced or moderately increased risk of death or serious respiratory morbidity at 22–26 months corrected age in those receiving AZM relative to placebo. Similarly, the 95% confidence interval for difference in death or NDI between treatment groups is broad (−2 to 34%). Importantly, we observed that infants who had lower respiratory tract Ureaplasma colonization in the neonatal period had persistent adverse pulmonary outcomes, including greater risk for the composite outcome death or serious respiratory morbidity, suggesting that these infants should be targeted in future trials.We conducted 22–26-month corrected age follow-up for this Phase IIb RCT to assess the potential impact of AZM therapy on long-term pulmonary and neurodevelopmental outcomes. We have previously published the primary efficacy outcome analysis showing that intravenous AZM 20 mg/kg for 3 days effectively eradicates 40 In the current follow-up study, we chose the composite outcome of death or serious respiratory morbidity defined by Jensen et al.34 as the primary outcome. The components of the serious respiratory morbidity definition could be ascertained from the electronic medical records for the majority of subjects and they represent meaningful clinical outcomes7 and are factors that impact parents’ perceptions of quality of life for their children41 and inform healthcare providers.5 Jensen et al.34 determined that a revised BPD definition that categorized lung disease severity according to mode of respiratory support at 36 weeks PMA rather than supplemental oxygen best predicted serious respiratory morbidity in the first 2 years of life in preterm infants born <27 weeks gestation.Since the widely used BPD definitions are poor predictors of subsequent respiratory illness later in childhood, consensus is lacking among neonatologists on which clinically meaningful short- and long-term endpoints should be targeted in clinical trials of BPD prevention.43 The potential for parental recall bias of respiratory symptoms such as wheezing has been debated in previous studies.45 To reduce recall bias in the current study, we used the validated Tucson Children’s Respiratory Study questionnaires administered by trained personnel at 4 timepoints during the first 2 years of life. Approximately two-thirds of parents reported family history of asthma and/or atopy. Respiratory medication use prevalence was ~65% in surviving children in both treatment arms with nebulized albuterol the most frequently reported medication. Respiratory medication use was similar to rates reported in other ELGAN cohorts during the first few years of life.43 Whether these medications were prescribed for BPD or viral infection-related wheezing is not known.Questionnaires that rely on parental recall of respiratory symptoms, medication use, and physician visits have been commonly used in studies of pulmonary outcomes in preterm infants.Ureaplasma respiratory tract colonization has been proposed as an etiologic factor in reactive airway disease in young infants. Wheezing in infants and children <3 years of age has been associated with isolation of Ureaplasma from the upper respiratory tract.46 There was no significant difference in parental-reported chronic cough or wheezing in children who were Ureaplasma tracheal aspirate positive compared to those children who had been tracheal aspirate negative or never intubated. In post hoc analysis of placebo-treated intubated infants with and without lower tract Ureaplasma colonization, Ureaplasma-colonized infants were discharged to home at later PMA, suggesting a more complicated NICU course in colonized infants.34 Although AZM has been proposed as a neuroprotective agent in neonatal animal models,47 there was no apparent benefit in neurodevelopmental measures by treatment group or when stratified by Ureaplasma status. Despite worse pulmonary morbidity, infants with lower respiratory tract Ureaplasma infection had similar rate of death or moderate–severe NDI as intubated infants without lower tract involvement or non-intubated infants. In multiple previous studies, BPD severity was a risk factor for adverse neurodevelopmental outcomes.8 However, in a recent single-center birth cohort, BSID-III cognitive scores were not associated with BPD severity.48We examined the impact of AZM treatment in the first few days of life on later NDI, a treatment effect that has not been previously reported. The rate of death or moderate-to-severe NDI in the current study cohort is similar to rates reported in other neonatal cohorts.49 The safety of AZM in preterm infants has been assessed in a systematic review of 11 neonatal RCTs and observational studies.17 The majority of adverse events in the neonatal period were related to prematurity and were assessed as unlikely associated with AZM treatment. Although infantile hypertrophic pyloric stenosis has been associated with AZM exposure in the first few weeks of life,51 only 4 cases were identified in 473 infants included in the systematic review and there were no cases in the current trial. In addition, AZM is pro-arrhythmogenic with prior reports of occurrences of QT-interval prolongation and torsade’s de pointes in adults52 but has not been observed in neonates treated with therapeutic doses.AZM has a low incidence of side effects in adults and children aged >2 years, primarily gastrointestinal symptoms.Ureaplasma positive from upper and/or lower airways, there was significantly greater serious respiratory morbidity in the AZM-assigned group than in the placebo-assigned group. A larger trial will be needed to determine whether this finding is directly related to neonatal AZM exposure or is due to random variation. This observation underscores the importance of delaying adopting AZM therapy to prevent BPD into clinical practice until a Phase III RCT is completed. There is an ongoing AZM therapy for chronic lung disease of prematurity (AZTEC) Phase III RCT of a 10-day course of AZM  that will enroll 796 preterm infants <30 weeks gestation to determine the safety and efficacy of this regimen to improve survival without BPD.53Long-term safety of neonatal AZM exposure has not been previously addressed. In our small sample of children who were Ureaplasma, but we had insufficient power to exclude small-to-moderate differences between the groups for long-term pulmonary and neurodevelopmental outcomes. To indicate the range of group differences that could not be ruled out with our data, we presented 95% confidence intervals. Also, we recognize that relationships suggested early in follow-up—close in time to characterization with regard to Ureaplasma or AZM treatment—can be expected to attenuate as other exposures such as viral illnesses and differences in home environment influence pulmonary and neurological outcomes, further eroding statistical power. Attrition at the 22–26-month corrected age assessment timepoint may have introduced ascertainment bias since higher rates of NDI are significantly correlated with increased loss to follow-up in a systematic review of 43 follow-up studies of ELGAN infants.54Our sample size had good power to detect a treatment effect on the primary outcome of clearance of Ureaplasma in the lower respiratory tract and inform the design of a future Phase III trial targeting Ureaplasma-colonized infants. An adequately powered Phase III clinical trial limited to ELGAN infants with PCR-confirmed lower respiratory tract Ureaplasma would determine whether or not a 3-day course of AZM is of clinical benefit to reduce short- and long-term pulmonary morbidity.The results of this trial extend the observation that mortality and prolonged respiratory support are concentrated in ELGANs who have Supplementary Information


We identified compounds with opposite gene expression signatures (ConnectivityMap data) compared to our TWAS results using the Kolmogorov-Smirnov test, Spearman and Pearson correlation. As symptom patterns are routinely assessed in clinical practice and could be used to provide targeted treatments, we identified MDD subtypes associated with TRD in UKB and analysed them using the same pipeline described for TRD. Anxious MDD  and MDD with weight gain (n = 4697) were associated with TRD. In the TWAS, two genes were significantly dysregulated . A muscarinic receptor antagonist was identified as top candidate for repurposing in TRD; inhibition of heat shock protein 90 was the main mechanism of action identified for anxious MDD, while modulators of metabolism such as troglitazone showed promising results for MDD with weight gain. This was the first TWAS of TRD and associated MDD subtypes. Our results shed light on possible pharmacological approaches in individuals with difficult-to-treat depression.Major depressive disorder (MDD) is the single largest contributor to global disability and up to 20–30% of patients do not respond to at least two antidepressants . This study leveraged imputed gene expression in TRD to perform a drug repurposing analysis. Among those with MDD, we defined TRD as having at least two antidepressant switches according to primary care records in UK Biobank (UKB). We performed a transcriptome-wide association study (TWAS) of TRD ( Major depressive disorder (MDD) is the single largest contributor to global disability and the main contributor to suicide deaths, which number close to 800,000 per year . AntidepMDD and antidepressant response have a heritable component , 8, the Drug repurposing guided by genetic findings is a promising approach to identify new candidate compounds for TRD and depression subtypes of interest, as selecting genetically supported targets could double the success rate in clinical development . PreviouTherefore, in the present study we analysed UK Biobank (UKB) data with the aim to: (1) identify gene expression changes associated with TRD and depression subtypes associated with TRD risk; (2) compare the disease-associated gene expression profiles with drug-induced gene expression to select compounds that show opposite patterns of expression and could counteract the pathogenetic alterations of TRD.We selected MDD subtypes associated with TRD and TRD itself to prioritize the identification of compounds potentially effective in cases of MDD poorly responsive to the available antidepressants and because previous studies have focused on MDD as a whole group , 16, 19.Each drug was prescribed for at least six consecutive weeks ;The time interval between the prescription of two consecutive drugs was no longer than 14 weeks (to ensure that treatment had not been suspended).TRD was defined using electronic health records (EHR) of primary care events in UKB as participants with MDD having at least two switches between different antidepressant drugs (independently from the class) satisfying the following criteria :Each druSecondly, we tested if any MDD subtype was associated with an increased risk of TRD, considering MDD with typical and atypical neurovegetative symptoms, MDD with weight gain, anxious MDD, psychotic, seasonal, peripartum, stress-related or reactive MDD and endogenous MDD. These depression subtypes were defined using primary care EHR of diagnostic codes and/or symptoms reported as part of the mental health questionnaire (MHQ), particularly those assessed by the Composite International Diagnostic Interview Short Form (CIDI-SF) ; cases op < 5e-324), particularly in cases who reported weight gain during their worst depressive episode (30.19 [SD = 5.56]). We did not adjust the analyses for BMI, because shared genetic factors and a bi-directional relationship have been reported between MDD and overweight/obesity [n = 54,974 after quality control). GWAS summary statistics of TRD vs healthy controls  were generated as part of a previous study [We performed a genome-wide association study (GWAS) of depression subtypes found to be associated with TRD using BGENIE v1.2 and imputed genotype dosages ; phenoty/obesity . We inclus study .http://gusevlab.org/projects/fusion/#reference-functional-data). We chose to use FUSION software because it compares several models when deriving SNP-weights to account for different architecture and it has in-built functionality for conditional and colocalization analyses. We did not focus our analyses exclusively on brain tissues because: (1) a high correlation between cis-eQTLs effects in blood and brain tissues has been demonstrated, as well as a gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL data with large sample sizes [SNP weights from distinct tissues and samples (of European ancestry) were used, applying the same procedure described in a recent study . As in tle sizes ; (2) MDDle sizes ; (3) Cmale sizes . The weile sizes –34.p = 1.37 × 10−6 in line with a previous study [A TWAS was performed for each phenotype of interest using FUSION, setting the transcriptome-wide significance at us study ; colocalus study  and are https://clue.io/query) to screen the available signatures and identify those to include in the following step (see next paragraph). To the best of our knowledge, Cmap represents the largest repository of compound-induced gene expression profiles in terms of number of available compounds and type of experimental conditions .As the high number of compound signatures (>130 K) available in ConnectivityMap (Cmap) and the lack of information to select a priori certain experimental conditions , we used the Cmap Query tool  to identify candidate signatures generating opposite transcriptional responses, since we do not know how many genes underlie TRD or depression subtypes [R2) [p value is calculated by comparing the similarity between the query and reference signature (KS test) to a null distribution of random queries and then it is adjusted for multiple testing  [We selected the compound signatures generating gene expression profiles most dissimilar to our top TWAS results, given the hypothesis that these could counteract the alterations observed in TRD and MDD subgroups of interest . Cmap casubtypes . This mesubtypes , althougpes [R2) . Cmap Qupes [R2) . To allote, FDR) .z-scores and repeating the same procedure above to determine average ranks. We performed 100 permutations for each signature–phenotype pair and combined the distribution of ranks under the null across all signature–phenotype pairs; the p value was calculated by comparing the distribution of the permuted ranks to the observed ranks.Selected signatures from the previous step were then examined using the approach described in a previous study that includes the R code made available by the authors , in ordez-score vectors representing gene expression levels [p < 0.10 ; (3) the signature corresponded to a compound (and not the genetic loss/gain of function perturbagens included in Cmap); (4) the corresponding compound was not an antidepressant or antipsychotic medication and did not have known toxicity or relevant side effects ; (5) the signature satisfied Cmap quality control criteria [For these analyses we downloaded the Expanded CMap LINCS Resource 2020 level 5 data which includes replicate-collapsed n levels . We applcriteria . If a siThese analyses were performed using the R code made available by  in R vern total = 5826 and 4697 after quality control), anxious MDD  and endogenous MDD   and ATP2A1 for depression with weight gain ; no significant features were identified for TRD. The top features (p < 5e-5) for each phenotype are described in Supplementary Table z-scores across tissues in Fig. We identified two transcriptome-wide significant signals: TMEM106B for depression with anxiety  and monoaminergic neurotransmission (7%). For anxious depression, modulation of cell survival–proliferation–differentiation was again the most common mechanism of action (15%), but interestingly inhibition of heat shock proteins (HSP) was the second one (10%). Candidate compounds for depression with weight gain included mostly modulators of metabolism (14%), such as peroxisome proliferator-activated receptor (PPAR) agonism. A relatively high proportion of the identified compounds had no reported mechanisms of action in the Cmap database .p < 0.05, which included zamifenacin (a muscarinic M3 and M5 receptor antagonist) and two molecules with unknown mechanism of action.For TRD, anxious and weight gain MDD, respectively, a total of 58, 35 and 18 compounds had at least one available expression signature passing quality control . The top results for each group are summarized in Table Four compounds showed permuted This study leveraged imputed gene expression profiles of TRD and associated depression subtypes to identify compounds showing opposite transcriptomic changes, which may have therapeutic effects in these groups as they show poor response to standard treatments.p < 5e-5) were significantly dysregulated in the same study  and two compounds with still unknown activity. Some antidepressants and atypical antipsychotics show M3 receptor antagonism, and scopolamine, a non-selective antimuscarinic drug, shows rapid antidepressant effects in TRD [Our screening of molecules for drug repurposing in TRD identified 76 compounds, one of which was shared with anxious MDD, two were antipsychotics, and six were identified also in a previous drug repurposing study for TRD , though s in TRD , 46. Hows in TRD , but thes in TRD . DantrolFor anxious depression, one of the 41 compounds identified in the screening phase was an approved antidepressant (agomelatine) and two were identified in the previously cited TRD repurposing study . The modp value in the drug ranking using the connectivity score, Spearman and Pearson correlation, and this analysis identified only one molecule with unknown mechanism of action (Table Among the 20 molecules identified in the screening step for MDD with weight gain, one was also significant in our previous study of drug repurposing in TRD . This waOur results should be interpreted in the light of the limitations of this study. The sample sizes included in the TWAS were relatively limited, as they were constrained to the number of cases available for each MDD subtype and TRD, and to the number of participants of European ancestry. The weights used in the TWAS were calculated based on existing eQTL datasets, which were often obtained in small samples, particularly for brain tissues in GTEx, though PsychENCODE is larger. On the other hand, the use of imputed gene expression from GWAS is much more feasible on a large scale than the direct measurement of gene expression levels. The tested tissues were selected based on the previous literature, however, the inclusion of 21 distinct SNP-weight sets from different tissues might capture noncausal genes . The resIn conclusion, our study identified two genes showing transcriptomic alterations in depression subtypes associated with TRD: TMEM106B in anxious MDD and ATP2A1 in MDD with weight gain; both genes had previous evidence of involvement in psychiatric traits and also metabolic traits in the case of ATP2A1. Our drug repurposing analyses suggested that the inhibition of HSP90 and the modulation of cell cytoskeleton may represent alternative strategies for the treatment of anxious MDD, while drugs modulating metabolism may be beneficial in MDD with weight gain. For the treatment of TRD, potentially useful pharmacological mechanisms included the antagonism of muscarinic receptors, the modulation of DNA methylation and calcium channels.Supplementary Methods-Table S1 - Figures.Supplementary Table 2.Supplementary Table 3.Supplementary Table 4.


The compound nature of large wildfires in combination with complex physical and biophysical processes affecting variations in hydroclimate and fuel conditions makes it difficult to directly connect wildfire changes over fire-prone regions like the western United States (U.S.) with anthropogenic climate change. Here we show that increasing large wildfires during autumn over the western U.S. are fueled by more fire-favorable weather associated with declines in Arctic sea ice during preceding months on both interannual and interdecadal time scales. Our analysis  demonstrates and explains the Arctic-driven teleconnection through regional circulation changes with the poleward-shifted polar jet stream and enhanced fire-favorable surface weather conditions. The fire weather changes driven by declining Arctic sea ice during the past four decades are of similar magnitude to other leading modes of climate variability such as the El Niño-Southern Oscillation that also influence fire weather in the western U.S. The western United States have seen an increase in wildfire activity in recent decades, the causes of which are not well understood. Here, the authors show that Arctic sea ice decline contributed to this increase through its influence on regional circulation which enhanced fire-favourable weather conditions. Both numbers and total burned areas of large wildfires  or fuel aridity in condition-limited fire regimes  where there is ample fuel supply14. Although there are multiple fire regimes across the western U.S., several previous studies have found substantial influence of global climate change on increasing forest wildfires over the past four decades through enhanced fuel aridity9 and a reduction of the high-elevation flammability barrier with upslope advance in montane forest fires15. Different characteristic scales of anthropogenic and natural processes also shed light on disentangling the fire-centered nexus between human and climate systems for extreme event detection and attribution. For instance, land use change and forest management with excessive fire exclusion and human suppression better explains a forest fire deficit in the western U.S. decoupled from climate and fire weather changes on centennial time scales since the middle 1800s, while the reconciled trends of increasing large fires and worsening fire weather in recent decades suggest an increasingly important role of anthropogenic climate change in modulating regional fire activity on shorter  time scales16 as discussed here.Large wildfires are an increasing threat to society and ecosystems over the western U.S., especially across the expanding wildland-urban interface (WUI) regions10 and other fire-prone regions worldwide19. However, a clear causal relationship with mechanistic understanding of complex climate-fire interactions in the Earth system can hardly be drawn from these relatively simple empirical models lack of interacting processes across the Earth’s subsystems ; those causality explanations are better provided by physically-based Earth system models (ESMs) with interactive fire components. In recent years, fire modeling in ESMs has advanced rapidly using various levels of model complexity to represent fire-related climate and vegetation processes20. These fire-enabled ESMs provide new tools for investigating the impact of anthropogenic climate change on global and regional fire activity through process-based physical and ecological pathways. For instance, Arctic sea ice has been declining dramatically since the late 1970s particularly in summer and autumn, which is closely related with much stronger warming in the Arctic than the global mean temperature as so-called Arctic amplification (AA)21. Several previous studies have suggested significant influence of Arctic sea-ice loss on regional fire weather such as surface air temperature and precipitation based on global and regional climate models25 or even annual wildfire activity in the western U.S. based on statistical analysis26, but a comprehensive and quantitative evaluation of the Arctic impact on regional burning activity and its role in the observed fire weather change is still lacking. Given increasing but still controversial evidence of emerging connections between high-latitude environmental change and mid-latitude weather extremes in both warm and cold seasons of the past few decades29, further exploration of the potential sea ice-fire teleconnection is worthwhile using latest fire-enabled ESMs.Fire weather variables such as temperature, vapor pressure deficit, and precipitation provide strong explanatory power for seasonal to multidecadal fire activity in empirically based statistical models developed for the western U.S.30. This teleconnection is further examined and corroborated across multiple ESMs participated in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6)31.In this work, we use a series of observation-/reanalysis-/model-based diagnostics and climate model sensitivity experiments to investigate the linkage between declining sea ice in the Arctic and worsening fire hazards in the western U.S. over the past four decades. We first identify an observation-based teleconnection linking regional fire weather and burning activity with Arctic sea-ice changes, and then design and run climate sensitivity experiments using a state-of-the-art fire model with improved fire modeling capability embedded in the Community Earth System model (CESM-RESFire)r = −0.68; p-value < 0.01) between declining sea-ice concentrations (SIC) over the Pacific sector of the Arctic  in preceding summer and autumn (July to October) and worsening fire weather conditions  atmospheric reanalysis of the global climate (ERA5)33; see Methods section) during the following autumn and early winter (September to December) over the western U.S.  from July to October in the 40-year control run with the multi-year average Arctic SIC/SST conditions corresponding to the observed minimum (hereafter SICexp−) and maximum (hereafter SICexp+) SIC years to isolate the impact of preceding Arctic sea-ice loss on regional fire weather and burning activity in the following autumn and early winter . The modeling results show an anomalous dipole pattern in the 500 hPa geopotential height field averaged over September-December (hereafter Z500) with cyclonic (negative) anomalies centered over Alaska and anticyclonic (positive) anomalies centered over the western U.S. in response to prescribed sea-ice reduction in preceding July to October Fig. . This anp-value = 0.01 based on a two-sided t-test for the 40 paired Z500i samples from the SICexp± experiments; the same test is also used for the following FFWI, burned area, fire occurrence, and fire size comparisons between the SICexp± experiments) concurrent with other regional weather changes including suppressed clouds and precipitation and increased incoming solar radiation over the western U.S.  with more frequent and intensified hot and dry surface weather conditions during autumn and early winter in SICexp−. Accordingly, such fire-favorable weather in SICexp− is conducive to more extensive burning activity over the western U.S. as suggested by expanded regional burned area  due to both increased fire occurrence  and enlarged fire size . A month-by-month comparison between SICexp− and SICexp+ also shows consistent changes in regional fire weather, fire occurrence, fire size, and total burned area in consecutive months after Arctic sea-ice declining, with the largest increase of regional total burned area by ~12.5% in November  in each experiment (see Methods). The statistical distributions of Z500i suggest a positive shift in SICexp−  between SIC− and SIC+ years shows strong but heterogeneous warming both near the surface and in the free troposphere over mid- and high-latitude regions, manifested by an enhanced (reduced) meridional temperature gradient ~60 °N 80 °N) in the lower and middle troposphere Fig. . This fe0 °N in t35. However, the complexity of multiple interactive pathways and processes in climate systems and relatively short observational records also increase the difficulty of detection and attribution of climate extreme events in the observed historical data. As mentioned above, the model-simulated warming and associated hydroclimate anomalies are generally weaker than the reanalysis-based composite difference because of the fixed climate forcing agents such as GHGs and extra-polar SST changes other than the local warming effect induced by Arctic sea-ice loss in the modeling sensitivity experiments. The missing global warming effect in the atmosphere and extra-polar oceans in the CESM modeling settings limits its capability to answer the second question about the importance of the Arctic-driven teleconnection effect in the observed fire weather changes associated with all climate variability and interactive processes.The synergistic effects of these multivariate fire weather changes following pre-conditioned peak fire season during climatologically hot and dry summer prolongs regional fire season and exacerbates burning severity in the subsequent autumn and early winter following diminished Arctic sea ice, making the prediction of fire hazards well-suited to an analysis of compound climate extreme events31 and its counterfactual counterpart with pre-industrial forcing (amip-piForcing or AMIP SSTs with control forcing)36 experiments in CMIP6 (see Methods). These two experiments share the same realistic and observationally-based SST and sea-ice surface conditions from 1979 to near present-day but expose model sensitivity to different anthropogenic forcing levels of GHGs, aerosols, and land use change by simulating the model response to time varying realistic forcing levels (as in the amip scenario) and to forcing levels held constant at pre-industrial levels (as in the amip-piForcing scenario). The differences between the SIC− and SIC+ years in both amip  on historical fire weather variability, we also examine the difference of climate responses between the Atmospheric Model Intercomparison Project (amip)37 based on the ERA5 reanalysis and the amip model ensemble to separate forced responses in regional fire weather due to other climate variability such as tropical ocean variations associated with ENSO (see Methods). The multi-field pattern filtering results show ENSO- and Arctic-driven hemispherical teleconnection patterns emerging in the first  filtering method”p-value < 0.01) and FFWI  also reproduce the reanalysis-based interannual and interdecadal variations in general, with comparable correlation coefficients among SIC, Z500i, and FFWI between the amip model ensemble and the reanalysis data  about the climate influence on compound extreme events such as the fire hazard discussed here. Our combined analyses based on both single forcing-oriented climate sensitivity experiments and all forcing-included ensemble historical modeling experiments enable us to understand the physical mechanism underlying the statistical relationship as well as its relative contributions to the observed fire weather changes. Massive Arctic sea-ice loss in summer and autumn strongly increases surface absorption of incoming solar radiation through the positive surface albedo feedback, resulting in a strong surface warming and strengthened upward turbulent heat fluxes into the lower troposphere over the sea-ice melted Arctic regions. This surface warming anomaly induces a cyclonic potential vorticity anomaly40 over the heating source and vicinity land regions like Alaska, which further enhances warm air advection from the ocean into downstream land regions like the western U.S. This dynamic-driven warming anomaly over the western U.S. helps to develop and strengthen an anticyclonic anomaly in the lower to middle troposphere of this region that manifests as a dipole pattern in conjunction with the cyclonic anomaly over the upstream regions like Alaska. This dipole pattern corresponds to a poleward-shifted polar jet stream with suppressed precipitation and elevated surface air temperature and vapor pressure deficit over the western U.S., all conducive to increased fuel aridity and more extensive burning during the following autumn and early winter in this region 43 and the Fire Model Intercomparison Project (FireMIP)44 have been designed and conducted, which help narrowing the knowledge gaps regarding the teleconnection linking high-latitude and mid-latitude regions and its role in increasing fire hazards.Although some interactive processes such as ocean-atmosphere coupling and fire-climate feedbacks are missing in the modeling experiments used in this study, previous studies have investigated the possible influence of those interactive processes and suggested consistent but amplified climate responses through ocean-atmosphere coupling45. Previous studies have identified strategies for coexistence with wildfires in a changing climate with escalating fire danger47. But Arctic sea ice has been projected to continuously decline and eventually diminish to a sea ice-free Arctic in September before the 2050s48, so more drastic changes might be anticipated. This study describes a mechanism indicating how the teleconnection between decreasing Arctic sea ice and worsening regional fire weather may be sustained and even strengthen over the next few decades, favoring more and larger wildfires across the western U.S. and making this region, especially the growing WUI areas, even more susceptible to destructive fire hazards. These implications may serve as motivation for more attention to adaptive resilience approaches including public awareness of fire risk and hazard mitigation, scientific fire risk and forest management, and sustainable residential and infrastructure development planning on fire-prone landscapes47.More extreme fire weather with increasing likelihood of large wildfires in autumn has become the new normal for western regions like California, a region projected to suffer more by the end of this century as has the clear decline in Arctic sea-ice coverage49. Daily and monthly meteorological variables including air temperature, 2-m relative humidity, wind speed and vectors, total precipitation rates, and geopotential heights used for the FFWI calculation and fire weather composite analysis are collected and processed based on the ERA5 reanalysis dataset33. We also analyzed the Canadian Forest Fire Weather Index (FWI)50 datasets that are calculated based on the ERA5 reanalysis data33 from the Global ECMWF Fire Forecast model (GEFF-ERA5)51 and the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA-2)52 reanalysis data from the Global Fire Weather Database (GFWED)53, respectively, as well as multiple observation- and reanalysis-based precipitation datasets from the Global Precipitation Climatology Project (GPCP v2.3)54, MERRA-252, Climate Forecast System Reanalysis (CFSR)55, ERA-Interim56, and the Japanese 55-year Reanalysis (JRA-55)57 for testing the robustness of the Arctic sea ice-fire teleconnection in Supplementary Table The 1° entclass1pt{minima58. We update the relative old MTBS fire data used in Dennison et al.2 and show the continuously increasing trends in both numbers and burned areas of large wildfires over the western U.S. in Supplementary Fig. The observational dataset of large wildfires 60, while the atmosphere component we use is the high-top Whole Atmosphere Community Climate Model (WACCM)61, which is a comprehensive atmospheric model with a well-resolved stratosphere by 70 vertical levels up to 140 km at a horizontal resolution of 1.9° (latitude) × 2.5° (longitude).We use a process-based CESM-RESFire model49 to generate initial conditions for two sensitivity runs. We then branch two climate sensitivity experiments  from July to December of each modeling year by perturbing SIC and SST in the Pacific sector of the Arctic  run with annually repeating prescribed climatological (1981–2010 average) SIC and SST from the HadISST dataset42. For the western U.S. region of interest in this study, the net fire feedback effect is almost negligible as shown in the Supplementary Fig. To focus on the sea-ice influence on fire, we turn off the fire feedback processes including online coupled fire emissions and fire-induced land cover change in the RESFire model. These feedback processes would exert detectable but secondary effects on global burning activity by either amplifying or damping regional burned area simulations as suggested by the comprehensive evaluation in our previous study31 and amip-piForcing36 experiments. There are 15 CMIP6 models 64 for measuring the weather influence on fire danger in the U.S. It is calculated based on surface air temperature, 2-m relative humidity, and surface wind speed with larger values implying higher fire risk or potential. FFWI is given by:FFWI10 and weekly to seasonal fire danger forecasts in the U.S.65. In comparison, FWI50 is a more sophisticated system based on multiple fuel moisture codes and fire behavior indices, which are derived from meteorological variables including surface air temperature, relative humidity, wind, and precipitation at local noon time. We choose FFWI in combination with precipitation rather than FWI for fire weather analysis in the main text because of its less stringent requirement for meteorological data inputs given limited weather/fuel data availability from daily-based climate model outputs. Using different fire weather indices or reanalysis datasets for analysis does not change the major finding of the identified teleconnection  method, which is a non-parametric way to estimate the probability density function of a random variable.We calculate the gridded FFWI based on the daily ERA5 reanalysis data and climate modeling outputs from CESM-RESFire and CMIP6 models. The regional average FFWI, BA, NFIRE, and FIREsize for the correlation and composite analysis in Figs. 68 is the time series of the leading combined Empirical Orthogonal Function (EOF) of five different variables  over the tropical Pacific basin . We use MEI for comparing and interpretating the identified S/NP forced responses. The S/NP1 timeseries in both original and detrended data show strong correlations with MEI p-value < 0.01, reconfirming the close connection between the two regions in terms of temporal variations of the two variables. To exclude the impact of long-term trends in both time series, we also conduct the same analysis based on the detrended time series in Supplementary Fig. r = −0.50; p-value < 0.01), suggesting a robust relationship on both interdecadal and interannual time scales.We first calculate the correlation coefficients between the time series of the regional and seasonal average FFWI  such as the seasonal/monthly FFWI composites in Fig. n = 6), model-simulated seasonal total burned area composites in Fig. n = 40), model-simulated regional average atmospheric and fire indices in Fig. n = 40), and seasonal mean fire weather variables in Fig. n = 6 for reanalysis-based data and n = 40 for model-based data). These data generally satisfy the assumptions of the t-test including normality and randomness of samples. If a p-value obtained from the t-test is no larger than a threshold, e.g., 69 to protecting against overstatement of multiple-testing results due to the influence of possible spatial correlation in Figs. p-values are no larger than a threshold level p-values:N is the number of testing grid cells and 69. For the modeling results from different CMIP6 climate modeling systems in Fig. We use a two-sided Student’s mentclass2pt{minimn = 10,000) and then repeatedly estimating the statistics such as the probability and intensity of extreme years based on the resampled data from each experiment  of these identified S/NPs and climate indices of interest (MEI and SIC in this application) to infer their driving forces. For example, in the S/NP filtering analysis based on the original ERA5 reanalysis and amip modeling data, S/NP1 and S/NP3 show good correlations with MEI  or different subsets of the amip models in the ensemble. The MEI-related pattern stays in S/NP1 as the strongest signal across different amip models, while the ranking of the SIC-related pattern varies between the second and the third  consists of two components driven by dynamic processes (DTCORE) and physical processes (PTTEND). The latter can be further decomposed into four major physical processes: moisture processes (DTCOND), longwave heating (QRL), shortwave heating (QRS), and vertical diffusion (DTV). There is one more physical process related to gravity wave drag (TTGW), which is small and negligible in the troposphere of modeling outputs. Therefore, the contribution to the regional average meridional temperature gradient anomaly (The sign and magnitude of Besides, note that the meridional temperature gradients remain positive in both the amip and amip-piForcing model ensembles (Supplementary Fig. Supplementary InformationPeer Review File


Cross-talk between the nervous system and the immune system is important in normal physiology and disease. This review discusses how neural signals regulate leukocyte migration around the body and within tissues and contributions by diverse neural signals to effective immune responses. Leukocyte trafficking between blood and tissues is an essential function of the immune system that facilitates humoral and cellular immune responses. Within tissues, leukocytes perform surveillance and effector functions via cell motility and migration toward sites of tissue damage, infection, or inflammation. Neurotransmitters that are produced by the nervous system influence leukocyte trafficking around the body and the interstitial migration of immune cells in tissues. Neural regulation of leukocyte dynamics is influenced by circadian rhythms and altered by stress and disease. This review examines current knowledge of neuro–immune interactions that regulate leukocyte migration and consequences for protective immunity against infections and cancer. With the exception of subsets of immune cells that permanently reside in peripheral tissue niches, most mature leukocytes spend much of their cellular lives trafficking around the body with the goal of identifying and eradicating microorganisms and malignant cells. Soluble and cell-associated signals direct leukocyte trafficking, tissue entry, and migration within tissues. These include chemokines, cytokines, and adhesion molecules expressed by vasculature, tissues, and other immune cells . In addiThe nervous system is composed of a somatic arm that consists of efferent motor nerves and afferent sensory nerves, and an autonomic branch that consists of parasympathetic and sympathetic nerves. Sensory nerves comprise at least five functional classes, including nociceptors that sense pain and noxious stimuli and signal via neurotransmitters, including the neuropeptides calcitonin gene-related peptide (CGRP) and substance P . Motor nMost tissues in the body are innervated to varying degrees by both sensory and autonomic nerves. Pertinent to neuro-immune communication is the observation that primary (bone marrow and thymus) and secondary (spleen and LN) lymphoid organs are innervated by sympathetic nerves . In LNs,In stark contrast to most other organs, there is no parasympathetic innervation in lymphoid organs, indicating that adrenergic signaling is a principal means of communication between the nervous system and the immune system . The twoThe adrenal medulla is the source of systemic adrenaline and little circulating noradrenaline. Most noradrenaline in blood comes from spillover from sympathetic nerve terminals . The adr1-adrenoceptor subtypes , α2 subtypes , and β-adrenoceptors  that are expressed on the surface of diverse cell types. α1-Adrenoceptors are expressed on smooth muscle cells and control vasoconstriction in blood vessels. α2-Adrenoceptors are involved in vasoconstriction (α2B) and presynaptic inhibition of noradrenaline release (α2A/C). The β-adrenoceptors also play diverse functional roles, including increased cardiac output (β1) and smooth muscle relaxation leading to dilatation of the airways (β2). Myeloid cells express both α- and β-adrenoceptors, whereas lymphocytes express mostly β2-adrenoceptors.The impact of the SNS on the immune system remains an area of intense interest. Catecholaminergic signaling occurs through G-protein–coupled α- and β-adrenergic receptors. The three main subtypes include α2-Adrenoceptor signaling induces intracellular increases in cAMP that activate protein kinase A, leading to transcriptional regulation of diverse pathways  may improve immunity. Indeed, a recent study directly examined this in volunteers receiving the tuberculosis vaccine bacillus Calmette-Guérin BCG; . Morning2-adrenoceptor agonists mostly increase circulating NK cells and CD8+ T lymphocytes, while α-adrenoceptor stimulation induces an increase in neutrophils (Increased catecholamine availability during stress or following pharmacological stimulation of adrenergic signaling also redirects the trafficking of leukocytes in the circulation . Neuronatrophils .The rapid release of leukocyte subsets into the circulation following adrenergic stimulation is assumed to result in the release of cells from so-called marginal pools and highly vascularized tissues such as the spleen and lungs. Indeed, within 5 min of injection of noradrenaline or the nonselective β-adrenoceptor agonist isoprenaline, leukocyte release from the spleen increases . InjectiGlucocorticoid hormones also induce changes in leukocyte trafficking. Injection of patients with hydrocortisone reduces the numbers of lymphocytes and monocytes in the blood after 4–6 h  coincidiThe changes in blood leukocyte numbers in response to injected catecholamines or glucocorticoids reflect changes induced in response to models of stress in rodents . LymphocTogether, these numerous observations suggest that activation of the HPA axis in response to stress leads to an increase in circulating adrenaline and glucocorticoids, mostly from endocrine tissues, that first mobilizes cells into circulation from marginal vascular pools and subsequently increases cell trafficking into tissues, where production of noradrenaline by local sympathetic nerves has an additional influence on cell trafficking and cell behavior (see the next section; Upon entering tissues from the blood, leukocytes move with dynamic motility and navigate diverse microenvironments. Motility is essential for leukocyte functions in tissues. Cells must adapt to various physical, cellular, extracellular matrix, and soluble cues within tissues . InterstRecent work has shown that catecholamines can also substantially regulate leukocyte motility in tissues . By usinThese observations illustrate that acute stress-induced release of catecholamines can rapidly restrict the motility of leukocytes. This pause in leukocyte behavior was short-lived in healthy animals but was sustained for hours in mice with a viral infection . Restric2-adrenoceptor stimulation in response to noradrenaline produced by local sympathetic nerves (2-adrenoceptor, thereby reducing leukocyte recruitment to the colon and ameliorating experimental colitis (In addition to the systemic control of leukocyte trafficking by catecholamines in the circulation, the innervation of peripheral tissues by sympathetic and sensory nerves provides many avenues for locally confined neuro-immune interactions. Clear examples of such interactions include the demonstration that muscularis macrophages in the intestine upregulate tissue repair genes, including arginase-1 via βc nerves . Optogen colitis .+ sensory nerves in the dermis (+ Trpv1+ nerves leads to CGRP release both locally and in adjacent skin through axon reflex activation of local Trpv1+ nerves. This was found to enhance local inflammation and to recruit IL-17+ γδT and CD4+ T cells (+ neurons in the skin, which release substance P and act via Mrgpra1 to drive the migration of CD301b+ DCs to draining LNs (+ GINIP+ neurons that produce the neuropeptide TAFA4 in response to UV skin damage (The activity of sensory nerves can also shape leukocyte responses in tissues niches. In the skin, macrophages and DCs interact with Trpv1e dermis , and sene dermis . Optogen T cells , providi T cells . Conversning LNs , and canning LNs . Substanning LNs . Anothern damage . This ren damage .+ nociceptors were also found to release CGRP and inhibit neutrophil recruitment, intravascular crawling behavior in the lung, and accumulation of lung γδ T cells during bacterial infection (Streptococcus pyogenes infection (Trpv1nfection , as wellnfection . Sensorynfection . Finallynfection , includinfection . These snfection .+ T cells in tumors (Recent studies have also revealed that peripheral nerves can influence tumor growth and metastasis , highlign tumors . Howevern tumors  suggestsn tumors . It is cNeural signals influence immune responses by guiding leukocyte functions, including the migration of cells around the body and within tissues. In particular, catecholamines direct circadian oscillations in immune cell trafficking and can impair dynamic leukocyte motility in tissues . There i