Oscillatory Coupling Between Neural and Cardiac Rhythms.

Oscillations serve a critical role in organizing biological systems. In the brain, oscillatory coupling is a fundamental mechanism of communication. The possibility that neural oscillations interact directly with slower physiological rhythms (e.g., heart rate, respiration) is largely unexplored and may have important implications for psychological functioning. Oscillations in heart rate, an aspect of heart rate variability (HRV), show remarkably robust associations with psychological health. Mather and Thayer proposed coupling between high-frequency HRV (HF-HRV) and neural oscillations as a mechanism that partially accounts for such relationships. We tested this hypothesis by measuring phase-amplitude coupling between HF-HRV and neural oscillations in 37 healthy adults at rest. Robust coupling was detected in all frequency bands. Granger causality analyses indicated stronger heart-to-brain than brain-to-heart effects in all frequency bands except gamma. These findings suggest that cardiac rhythms play a causal role in modulating neural oscillations, which may have important implications for mental health.

Assessing the post hoc effectiveness of tixagevimab-cilgavimab for prevention of SARS-CoV-2 infections in solid organ transplant recipients.

BACKGROUND: Tixagevimab-cilgavimab (Tix-Cil) was authorized for prophylaxis against COVID-19 in immunocompromised patients from December 2021 through January 2023. Real-world effectiveness for solid organ transplant (SOT) recipients has been unclear. METHODS: We enrolled 911 SOT recipients into a longitudinal COVID-19 serology study, of whom 381 (42%) received ≥1 dose of Tix-Cil. We collected and analyzed data on incident SARS-CoV-2 infections and antibody kinetics for all patients from January 2022 to March 2023, including periods dominated by Omicron BA and BQ subvariants. RESULTS: Over 253 ± 131 days of follow-up, there were 324 new-onset SARS-CoV-2 infections: 117 (31%) in Tix-Cil treated and 207 (39%) in Tix-Cil untreated patients (p = .012). In analyses adjusting for demographic, clinical, and COVID-19 exposure factors, any Tix-Cil treatment was associated with lower infection risk (OR 0.52, 95% CI 0.27-0.96, p = .039) throughout the surveillance period including when more resistant BQ.1 and BQ.1.1 subvariants had emerged (12/1/2022 onwards). Among treated patients, receiving a Tix-Cil dose was associated with substantial and sustained increase in anti-spike IgG antibody and angiotensin-converting enzyme 2 binding inhibition levels (Abbott Architect assay) that together also demonstrated association with lower infection risk (p = .042). During the full surveillance period, the frequency of infections requiring hospitalization was low overall (N = 26, 2.9% of the total cohort) and not significantly different between Tix-Cil recipients (N = 12, 3.2% of treated patients) and non-Tix-Cil recipients (N = 14, 2.6% of untreated patients) with unadjusted p = .31 for between-group difference. CONCLUSION: In a large cohort of SOT recipients, we found that Tix-Cil reduced infection risk even amidst emergent Omicron subvariants. Additionally, the extent of measurable humoral response to Tix-Cil may indicate relative effectiveness. Pre-exposure monoclonal antibody therapy may represent a strategy that will continue to offer clinical benefit for immunocompromised persons who are known to derive limited protection from vaccinations.

A minimally disruptive method for measuring water potential in planta using hydrogel nanoreporters.

Leaf water potential is a critical indicator of plant water status, integrating soil moisture status, plant physiology, and environmental conditions. There are few tools for measuring plant water status (water potential) in situ, presenting a critical barrier for developing appropriate phenotyping (measurement) methods for crop development and modeling efforts aimed at understanding water transport in plants. Here, we present the development of an in situ, minimally disruptive hydrogel nanoreporter (AquaDust) for measuring leaf water potential. The gel matrix responds to changes in water potential in its local environment by swelling; the distance between covalently linked dyes changes with the reconfiguration of the polymer, leading to changes in the emission spectrum via Förster Resonance Energy Transfer (FRET). Upon infiltration into leaves, the nanoparticles localize within the apoplastic space in the mesophyll; they do not enter the cytoplasm or the xylem. We characterize the physical basis for AquaDust's response and demonstrate its function in intact maize (Zea mays L.) leaves as a reporter of leaf water potential. We use AquaDust to measure gradients of water potential along intact, actively transpiring leaves as a function of water status; the localized nature of the reporters allows us to define a hydraulic model that distinguishes resistances inside and outside the xylem. We also present field measurements with AquaDust through a full diurnal cycle to confirm the robustness of the technique and of our model. We conclude that AquaDust offers potential opportunities for high-throughput field measurements and spatially resolved studies of water relations within plant tissues.

Mouse Adenovirus Type 1 Persistence Exacerbates Inflammation Induced by Allogeneic Bone Marrow Transplantation.

Bone marrow transplantation (BMT) recipients are at risk for substantial morbidity and mortality from human adenovirus infections, often in the setting of reactivation of persistent virus. Human adenovirus persistence in mucosal lymphocytes has been described, but specific cellular reservoirs of persistence and effects of persistence on host responses to unrelated stimuli are not completely understood. We used mouse adenovirus type 1 (MAV-1) to characterize persistence of an adenovirus in its natural host and test the hypothesis that persistence increases complications of BMT. Following intranasal infection of C57BL/6J mice, MAV-1 DNA was detected in lung, mediastinal lymph nodes, and liver during acute infection at 7 days postinfection (dpi), and at lower levels at 28 dpi that remained stable through 150 dpi. Expression of early and late viral transcripts was detected in those organs at 7 dpi but not at later time points. MAV-1 persistence was not affected by deficiency of IFN-γ. We detected no evidence of MAV-1 reactivation in vivo following allogeneic BMT of persistently infected mice. Persistent infection did not substantially affect mortality, weight loss, or pulmonary inflammation following BMT. However, T cell infiltration and increased expression of pro-inflammatory cytokines consistent with graft-versus-host disease (GVHD) were more pronounced in livers of persistently infected BMT mice than in uninfected BMT mice. These results suggest that MAV-1 persists in multiple sites without detectable evidence of ongoing replication. Our results indicate that MAV-1 persistence alters host responses to an unrelated challenge, even in the absence of detectable reactivation. IMPORTANCE Long-term persistence in an infected host is an essential step in the life cycle of DNA viruses. Adenoviruses persist in their host following acute infection, but the nature of adenovirus persistence remains incompletely understood. Following intranasal infection of mice, we found that MAV-1 persists for a prolonged period in multiple organs, although we did not detect evidence of ongoing replication. Because BMT recipients are at risk for substantial morbidity and mortality from human adenovirus infections, often in the setting of reactivation of persistent virus in the recipient, we extended our findings using MAV-1 infection in a mouse model of BMT. MAV-1 persistence exacerbated GVHD-like inflammation following allogeneic BMT, even in the absence of virus reactivation. This novel finding suggests that adenovirus persistence has consequences, and it highlights the potential for a persistent adenovirus to influence host responses to unrelated challenges.

From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data.

Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in "data desert" regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I-Harnessing theory.

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question-How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

Rapid response of nonstructural carbohydrate allocation and photosynthesis to short photoperiod, low temperature, or elevated CO2 in Pinus strobus.

During autumn, decreasing photoperiod and temperature temporarily perturb the balance between carbon uptake and carbon demand in overwintering plants, requiring coordinated adjustments in photosynthesis and carbon allocation to re-establish homeostasis. Here we examined adjustments of photosynthesis and allocation of nonstructural carbohydrates (NSCs) following a sudden shift to short photoperiod, low temperature, and/or elevated CO2 in Pinus strobus seedlings. Seedlings were initially acclimated to 14 h photoperiod (22/15°C day/night) and ambient CO2 (400 ppm) or elevated CO2 (800 ppm). Seedlings were then shifted to 8 h photoperiod for one of three treatments: no temperature change at ambient CO2 (22/15°C, 400 ppm), low temperature at ambient CO2 (12/5°C, 400 ppm), or no temperature change at elevated CO2 (22/15°C, 800 ppm). Short photoperiod caused all seedlings to exhibit partial nighttime depletion of starch. Short photoperiod alone did not affect photosynthesis. Short photoperiod combined with low temperature caused hexose accumulation and repression of photosynthesis within 24 h, followed by a transient increase in nonphotochemical quenching (NPQ). Under long photoperiod, plants grown under elevated CO2 exhibited significantly higher NSCs and photosynthesis compared to ambient CO2 plants, but carbon uptake exceeded sink capacity, leading to elevated NPQ; carbon sink capacity was restored and NPQ relaxed within 24 h after shift to short photoperiod. Our findings indicate that P. strobus rapidly adjusts NSC allocation, not photosynthesis, to accommodate short photoperiod. However, the combination of short photoperiod and low temperature, or long photoperiod and elevated CO2 disrupts the balance between photosynthesis and carbon sink capacity, resulting in increased NPQ to alleviate excess energy.

One size doesn't fit all: Attitudes towards work modify the relation between parental leave length and postpartum depression.

The present study aimed to investigate the relationship between parental leave length and maternal depressive symptoms at six- and twelve-months postpartum and whether this relation was influenced by women's attitudes towards leave, whether leave was paid or unpaid, and the reason they returned to work. The sample included 115 working women recruited during pregnancy as part of a larger longitudinal study. Analyses revealed that maternal attitudes toward leave influenced the association between leave length and depressive symptoms. Specifically, longer leaves were associated with increased depressive symptoms for women who missed their previous activities at work. Furthermore, women who missed work and had leave for 16 weeks or more, exhibited higher depressive symptoms at six- and twelve-months. Last, results also indicated that women who returned to work solely for monetary reasons exhibited more depressive symptoms at six-months postpartum than those who returned to work for other reasons. This study is among the first to show that women's attitudes towards parental leave and their individual reasons for returning to work are important factors to consider that may have potential implications for parental leave policies.

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data.

We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface (API) and command-line tool for high-dimensional mass spectrometry data analysis workflows that offers ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section (CCS) calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation; algorithm implementations simultaneously utilize all dimensions to (i) offer greater separation between features, thus improving detection sensitivity, (ii) increase alignment/feature matching confidence among data sets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS metabolomics data to illustrate the advantages of a multidimensional approach in each data processing step.

A Single Fasting Exhaled Methane Level Correlates With Fecal Methanogen Load, Clinical Symptoms and Accurately Detects Intestinal Methanogen Overgrowth.

INTRODUCTION: A 2-hour breath test is the gold standard for diagnosing intestinal methanogen overgrowth (IMO). This method can be cumbersome especially if used repetitively to monitor treatment response. Therefore, we aimed to assess the reliability of a fasting single methane measurement (SMM) in diagnosing IMO and its utility as a biomarker to monitor treatment response in subjects with IMO. METHODS: First, we calculated the test characteristics of SMM compared with lactulose and glucose breath test in 2 large-scale retrospective cohorts. Second, the symptomology associated with SMM using various cutoffs was analyzed. Third, in a double-blind randomized control trial, the temporal stability of SMM levels in subjects taking placebo was analyzed. Fourth, stool Methanobrevibacter smithii loads were quantified using quantitative polymerase chain reaction and compared with SMM levels. Last, the change in SMM over time during antibiotic therapy was analyzed. RESULTS: Using the cutoff of SMM ≥10 ppm, SMM had a sensitivity of 86.4% and specificity of 100% for diagnosing IMO on the glucose and lactulose breath tests and was associated with constipation (5.65 ± 3.47 vs 4.32 ± 3.62, P = 0.008). SMM remained stable for 14 weeks without treatment (P = 0.45), and antibiotics lead to a decrease in SMM after 2 days (P < 0.0001). SMM was positively associate with stool M. smithii load (R = 0.65, P < 0.0001). DISCUSSION: Fasting SMM ≥10 ppm seems to accurately diagnose IMO, is associated with constipation, and correlates with stool M. smithii. SMM seems to be stable without treatment and decreases after antibiotics. SMM may be a useful test to diagnose IMO and monitor treatment response.

A Smartphone Application Using Artificial Intelligence Is Superior To Subject Self-Reporting When Assessing Stool Form.

INTRODUCTION: Stool form assessment relies on subjective patient reports using the Bristol Stool Scale (BSS). In a novel smartphone application (app), trained artificial intelligence (AI) characterizes digital images of users' stool. In this study, we evaluate this AI for accuracy in assessing stool characteristics. METHODS: Subjects with diarrhea-predominant irritable bowel syndrome image-captured every stool for 2 weeks using the app, which assessed images for 5 visual characteristics (BSS, consistency, fragmentation, edge fuzziness, and volume). In the validation phase, using 2 expert gastroenterologists as a gold standard, sensitivity, specificity, accuracy, and diagnostic odds ratios of subject-reported vs AI-graded BSS scores were compared. In the implementation phase, agreements between AI-graded and subject-reported daily average BSS scores were determined, and subject BSS and AI stool characteristics scores were correlated with diarrhea-predominant irritable bowel syndrome symptom severity scores. RESULTS: In the validation phase (n = 14), there was good agreement between the 2 experts and AI characterizations for BSS (intraclass correlation coefficients [ICC] = 0.782-0.852), stool consistency (ICC = 0.873-0.890), edge fuzziness (ICC = 0.836-0.839), fragmentation (ICC = 0.837-0.863), and volume (ICC = 0.725-0.851). AI outperformed subjects' self-reports in categorizing daily average BSS scores as constipation, normal, or diarrhea. In the implementation phase (n = 25), the agreement between AI and self-reported BSS scores was moderate (ICC = 0.61). AI stool characterization also correlated better than subject reports with diarrhea severity scores. DISCUSSION: A novel smartphone application can determine BSS and other visual stool characteristics with high accuracy compared with the 2 expert gastroenterologists. Moreover, trained AI was superior to subject self-reporting of BSS. AI assessments could provide more objective outcome measures for stool characterization in gastroenterology.

Methanogens and Hydrogen Sulfide Producing Bacteria Guide Distinct Gut Microbe Profiles and Irritable Bowel Syndrome Subtypes.

INTRODUCTION: Irritable bowel syndrome (IBS) includes diarrhea-predominant (IBS-D) and constipation-predominant (IBS-C) subtypes. We combined breath testing and stool microbiome sequencing to identify potential microbial drivers of IBS subtypes. METHODS: IBS-C and IBS-D subjects from 2 randomized controlled trials (NCT03763175 and NCT04557215) were included. Baseline breath carbon dioxide, hydrogen (H 2 ), methane (CH 4 ), and hydrogen sulfide (H 2 S) levels were measured by gas chromatography, and baseline stool microbiome composition was analyzed by 16S rRNA sequencing. Microbial metabolic pathways were analyzed using Kyoto Encyclopedia of Genes and Genomes collection databases. RESULTS: IBS-C subjects had higher breath CH 4 that correlated with higher gut microbial diversity and higher relative abundance (RA) of stool methanogens, predominantly Methanobrevibacter , as well as higher absolute abundance of Methanobrevibacter smithii in stool. IBS-D subjects had higher breath H 2 that correlated with lower microbial diversity and higher breath H 2 S that correlated with higher RA of H 2 S-producing bacteria, including Fusobacterium and Desulfovibrio spp. The predominant H 2 producers were different in these distinct microtypes, with higher RA of Ruminococcaceae and Christensenellaceae in IBS-C/CH 4 + (which correlated with Methanobacteriaceae RA) and higher Enterobacteriaceae RA in IBS-D. Finally, microbial metabolic pathway analysis revealed enrichment of Kyoto Encyclopedia of Genes and Genomes modules associated with methanogenesis and biosynthesis of methanogenesis cofactor F420 in IBS-C/CH 4 + subjects, whereas modules associated with H 2 S production, including sulfate reduction pathways, were enriched in IBS-D. DISCUSSION: Our findings identify distinct gut microtypes linked to breath gas patterns in IBS-C and IBS-D subjects, driven by methanogens such as M. smithii and H 2 S producers such as Fusobacterium and Desulfovibrio spp, respectively.

The physiological basis for estimating photosynthesis from Chla fluorescence.

Solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIFPSII ) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level. The MLR-SIF model is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIFPSII . Once inferred from direct observables of SIF, SIFPSII provides 'parameter savings' to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.

ALT Levels in Treatment-Naive, Chronic Hepatitis B Patients with Concurrent Fatty Liver Disease: A US Nationwide Study.

INTRODUCTION: Treatment criteria for chronic hepatitis B (CHB) relies on ALT, which can be impacted by concurrent nonalcoholic fatty liver disease (NAFLD), but ALT data on patients with CHB and NAFLD are limited. We aimed to characterize ALT distribution in untreated CHB patients with NAFLD. METHODS: We retrospectively analyzed untreated US adults with CHB (533 with NAFLD, 3,172 without NAFLD) using the Clinformatics™ Data Mart Database (2003-2019). The main outcome was ALT elevation (>1× upper limit of normal, 35/25 U/L for men/women, respectively). Secondary outcomes were advanced fibrosis (via FIB-4 index) and factors associated with fibrosis. RESULTS: The majority of patients were Asian (61.0%) and hepatitis B e-antigen (HBeAg)-negative (90.4%). Patients with CHB and NAFLD were older (57.2 vs. 49.5 years, p < 0.001), more likely male (59.3% vs. 46.2%, p < 0.001), with higher percentages of advanced fibrosis (3.6% vs. 2.6%, p < 0.001) than those with CHB alone. CHB-NAFLD patients were more likely to have elevated ALT than those with CHB only, but this difference was only significant among those with low hepatitis B virus (HBV) DNA (38.1% vs. 25.6%, p < 0.001), not those with higher HBV DNA (>2,000 IU/mL). After adjusting for HBeAg, HBV DNA, and diabetes, NAFLD was not independently associated with advanced fibrosis (odds ratio 1.18, 95% confidence interval: 0.30-4.59, p = 0.81). DISCUSSION: CHB-NAFLD patients with HBV DNA below treatment threshold were more likely to have elevated ALT but not those with higher HBV DNA, suggesting that ALT threshold does not need to be raised for antiviral eligibility for CHB with NAFLD.

Exhaled Methane Is Associated with a Lower Heart Rate.

BACKGROUND: In humans, methane (CH4) is exclusively produced by the intestinal microbiota and has been implicated in several conditions including cardiovascular disease. After microbial production of CH4 in the gut, it steadily crosses into the systemic circulation and reaches the lungs where it can be detected in the exhaled breath, as a surrogate measure for intestinal CH4 production. Recent reports have shown an association between CH4 and vagal dysfunction as well as the inhibition of CH4 activity on ileal contractions with atropine, suggesting its action on the parasympathetic nervous system. Given these findings, we hypothesized that CH4 may be affecting resting heart rate (HR) based on the potential effect of CH4 on the vagus nerve. OBJECTIVES: Given its possible role in the parasympathetic nervous system, we aimed to study the relationship between breath CH4 and resting HR in humans. Additionally, we performed a longitudinal study analyzing the change in HR and its association with breath CH4 over time. METHODS: First, we reviewed 1,126 subjects and compared HR in subjects with detectable and undetectable breath CH4. Second, we performed a post hoc analysis of a randomized control trial to compare the change in HR for those who had an increase in breath CH4 versus those that had a decrease in breath CH4 over 14 weeks. Last, we assessed whether a larger decrease in CH4 is associated with a larger increase in HR over time. RESULTS: In the retrospective cohort, subjects with detectable CH4 had a lower HR compared to those with undetectable CH4 (73.0 ± 0.83 vs. 76.0 ± 0.44 beats/min, p = 0.01). In the post hoc analysis, a decrease in CH4 over time was associated with an increase in HR (median ∆ = 6.5 ± 8.32 beats/min, p = 0.0006). Last, we demonstrated a biological gradient whereby a larger drop in CH4 was associated with a greater increase in HR (R = -0.31, p = 0.03). CONCLUSION: Our findings suggest a potential role for the microbiome (and specifically CH4 from methanogens) to regulate HR. Considering these findings, mechanistic studies are warranted to further investigate this potential novel microbiome-neurocardiac axis.

Champions of winter survival: cold acclimation and molecular regulation of cold hardiness in evergreen conifers.

Evergreen conifers are champions of winter survival, based on their remarkable ability to acclimate to cold and develop cold hardiness. Counterintuitively, autumn cold acclimation is triggered not only by exposure to low temperature, but also by a combination of decreasing temperature, decreasing photoperiod and changes in light quality. These environmental cues control a network of signaling pathways that coordinate cold acclimation and cold hardiness in overwintering conifers, leading to cessation of growth, bud dormancy, freezing tolerance and changes in energy metabolism. Advances in genomic, transcriptomic and metabolomic tools for conifers have improved our understanding of how trees sense and respond to changes in temperature and light during cold acclimation and the development of cold hardiness, but there remain considerable gaps deserving further research in conifers. In the first section of this review, we focus on the physiological mechanisms used by evergreen conifers to adjust metabolism seasonally and to protect overwintering tissues against winter stresses. In the second section, we review how perception of low temperature and photoperiod regulate the induction of cold acclimation. Finally, we explore the evolutionary context of cold acclimation in conifers and evaluate challenges imposed on them by changing climate and discuss emerging areas of research in the field.

Mass Spectrometry Adduct Calculator.

We describe the Mass Spectrometry Adduct Calculator (MSAC), an automated Python tool to calculate the adduct ion masses of a parent molecule. Here, adduct refers to a version of a parent molecule [M] that is charged due to addition or loss of atoms and electrons resulting in a charged ion, for example, [M + H]+. MSAC includes a database of 147 potential adducts and adduct/neutral loss combinations and their mass-to-charge ratios (m/z) as extracted from the NIST/EPA/NIH Mass Spectral Library (NIST17), Global Natural Products Social Molecular Networking Public Spectral Libraries (GNPS), and MassBank of North America (MoNA). The calculator relies on user-selected subsets of the combined database to calculate expected m/z for adducts of molecules supplied as formulas. This tool is intended to help researchers create identification libraries to collect evidence for the presence of molecules in mass spectrometry data. While the included adduct database focuses on adducts typically detected during liquid chromatography-mass spectrometry analyses, users may supply their own lists of adducts and charge states for calculating expected m/z. We also analyzed statistics on adducts from spectra contained in the three selected mass spectral libraries. MSAC is freely available at https://github.com/pnnl/MSAC.

The Complete Genome Sequence of Xanthomonas theicola, the Causal Agent of Canker on Tea Plants, Reveals Novel Secretion Systems in Clade-1 Xanthomonads.

Xanthomonas theicola is the causal agent of bacterial canker on tea plants. There is no complete genome sequence available for X. theicola, a close relative of the species X. translucens and X. hyacinthi, thus limiting basic research for this group of pathogens. Here, we release a high-quality complete genome sequence for the X. theicola type strain, CFBP 4691T. Single-molecule real-time sequencing with a mean coverage of 264× revealed two contigs of 4,744,641 bp (chromosome) and 40,955 bp (plasmid) in size. Genome mining revealed the presence of nonribosomal peptide synthases, two CRISPR systems, the Xps type 2 secretion system, and the Hrp type 3 secretion system. Surprisingly, this strain encodes an additional type 2 secretion system and a novel type 3 secretion system with enigmatic function, hitherto undescribed for xanthomonads. Four type 3 effector genes were found on complete or partial transposons, suggesting a role of transposons in effector gene evolution and spread. This genome sequence fills an important gap to better understand the biology and evolution of the early-branching xanthomonads, also known as clade-1 xanthomonads.

Surface Functionalization of Black Phosphorus with Nitrenes: Identification of P=N Bonds by Using Isotopic Labeling.

Surface functionalization of two-dimensional crystals is a key path to tuning their intrinsic physical and chemical properties. However, synthetic protocols and experimental strategies to directly probe chemical bonding in modified surfaces are scarce. Introduced herein is a mild, surface-specific protocol for the surface functionalization of few-layer black phosphorus nanosheets using a family of photolytically generated nitrenes (RN) from the corresponding azides. By embedding spectroscopic tags in the organic backbone, a multitude of characterization techniques are employed to investigate in detail the chemical structure of the modified nanosheets, including vibrational, X-ray photoelectron, solid state 31 P NMR, and UV-vis spectroscopy. To directly probe the functional groups introduced on the surface, R fragments were selected such that in conjunction with vibrational spectroscopy, 15 N-labeling experiments, and DFT methods, diagnostic P=N vibrational modes indicative of iminophosphorane units on the nanosheet surface could be conclusively identified.

Variation in the phenology of photosynthesis among eastern white pine provenances in response to warming.

In higher-latitude trees, temperature and photoperiod control the beginning and end of the photosynthetically active season. Elevated temperature (ET) has advanced spring warming and delayed autumn cooling while photoperiod remains unchanged. We assessed the effects of warming on the length of the photosynthetically active season of three provenances of Pinus strobus L. seedlings from different latitudes, and evaluated the accuracy of the photochemical reflectance index (PRI) and the chlorophyll/carotenoid index (CCI) for tracking the predicted variation in spring and autumn phenology of photosynthesis among provenances. Seedlings from northern, local and southern P. strobus provenances were planted in a temperature-free-air-controlled enhancement (T-FACE) experiment and exposed to ET (+1.5/3°C; day/night). Over 18 months, we assessed photosynthetic phenology by measuring chlorophyll fluorescence, gas exchange, leaf spectral reflectance and pigment content. During autumn, all seedlings regardless of provenance followed the same sequence of phenological events with the initial downregulation of photosynthesis, followed by the modulation of non-photochemical quenching and associated adjustments of zeaxanthin pool sizes. However, the timing of autumn downregulation differed between provenances, with delayed onset in the southern provenance (SP) and earlier onset in the northern relative to the local provenance, indicating that photoperiod at the provenance origin is a dominant factor controlling autumn phenology. Experimental warming further delayed the downregulation of photosynthesis during autumn in the SP. A provenance effect during spring was also observed but was generally not significant. The vegetation indices PRI and CCI were both effective at tracking the seasonal variations of energy partitioning in needles and the differences of carotenoid pigments indicative of the stress status of needles. These results demonstrate that PRI and CCI can be useful tools for monitoring conifer phenology and for the remote monitoring of the length of the photosynthetically active season of conifers in a changing climate.