The Yarmouk tributary to the Jordan river II: Infrastructure impeding the transformation of equitable transboundary water arrangements

This article explores the ways in which key components of infrastructure built on the Yarmouk tributary to the Jordan River induce or impede the transformation of existing transboundary water arrangements. Focussing on the Jordanian-Israeli Adassiyeh Weir and on the Jordanian-Syrian Wehdeh Dam, the article interprets archival documents, official river-gauging data, and interviews through a frame that highlights depoliticisation by hydrocracies within the politics of international infrastructure. The weir is found to be operated in a manner that prioritises Jordan's commitment to Israel when flows are low, and to be designed to bound the volume that Jordan can make use of during low or very high flows. The dam appears oversized but regulates the flow to the downstream weir when its reservoir does not lie empty. The design and operation of the infrastructure is found to partially and selectively depoliticise contentious transboundary water issues in a manner that privileges the more powerful actors. Transformation of the arrangements is impeded as the distribution and use of the flows is not questioned by the water authorities or the international diplomatic community, and alternative arrangements are not considered

The Yarmouk tributary to the Jordan river I: Agreements impeding equitable transboundary water arrangements

This article explores the ways in which two international water agreements on the Yarmouk tributary to the Jordan River induce or impede transformation to equitable transboundary water arrangements. The agreements in question were reached between Jordan and Syria in 1987, and between Jordan and Israel in 1994. Following a brief review of theory and a summary of the body of knowledge on 'model' agreements, the article combines official river-gauging data with interviews and textual analysis to query the text and role of the agreements, particularly in relation to key dams and other infrastructure. Both agreements are found to i) lack important clauses that could govern groundwater abstraction, environmental concerns, water quality, and the ability to adapt to changing water quality, availability and need; and ii) include both ambiguous and rigid clauses that result in generally inequitable allocation of water and thus of the benefits derived from its use. Due to their omissions and to their reflection of the asymmetries in power between the states, both agreements are found to be 'blind' to existing use, to be incapable of dealing with urgent governance needs, and to impede more equitable arrangements

Evaluating Differences of Erosion Patterns in Natural and Anthropogenic Basins through Scenario Testing: A Case Study of the Claise, France and Nahr Ibrahim, Lebanon

This study assessed soil erosion risks of two basins representing different geographical, topographical, climatological and land occupation/management settings. A comparison and an evaluation of site-specific factors influencing erosion in the French Claise and the Lebanese Nahr Ibrahim basins were performed. The Claise corresponds to a natural park with a flat area and an oceanic climate, and is characterized by the presence of 2179 waterbodies (mostly ponds) considered as hydro-sedimentary alternating structures, while Nahr Ibrahim represents an orographic Mediterranean basin characterized by a random unequal land occupation distribution. The Claise was found to be under 12.48% no erosion (attributed to the dense pond network), 65.66% low, 21.68% moderate and 0.18% high erosion risks; while Nahr Ibrahim was found to be under 4, 39.5 and 56.4%, low, moderate and high erosion risks, along with 66% land degradation determined from the intersection of land capability and land occupation maps. Under the alternative scenario for the Claise where ponds were considered dried, erosion risks became 1.12, 0.52, 76.8 and 21.56%, no erosion, low, moderate and high risks, respectively. For Nahr Ibrahim, and following the Land Degradation Neutrality intervention, high erosion risks decreased by 13.9%, while low and moderate risks increased by 3 and 10.8%

Diagnosis of Histoplasmosis Using the MVista Histoplasma Galactomannan Antigen Qualitative Lateral Flow–Based Immunoassay: A Multicenter Study

Background: Accurate and timely methods for the diagnosis of histoplasmosis in resource-limited countries are lacking. Histoplasma antigen detection by enzyme immunoassay (EIA) is widely used in the United States (US) but not in resource-limited countries, leading to missed or delayed diagnoses and poor outcomes. Lateral flow assays (LFAs) can be used in this setting. Methods: Frozen urine specimens were submitted to MiraVista diagnostics for antigen testing from 3 medical centers in endemic areas of the US. They were blinded and tested for the MVista Histoplasma LFA. Patients were classified as controls or cases of histoplasmosis. Cases were divided into proven or probable; pulmonary or disseminated; immunocompetent or immunosuppressed; and mild, moderate, or severe. Results: Three hundred fifty-two subjects were enrolled, including 66 cases (44 proven, 22 probable) and 286 controls. Most of the cases were immunocompromised (71%), and 46 had disseminated and 20 had pulmonary histoplasmosis. Four cases were mild, 42 moderate, and 20 severe. LFA and EIA were highly concordant (κ = 0.84). Sensitivity and specificity of the LFA were 78.8% and 99.3%, respectively. LFA sensitivity was higher in proven cases (93.2%), patients with disseminated (91.3%), moderate (78.6%), and severe disease (80%), and those with galactomannan levels >1.8 ng/mL (97.8%). Specificity was 99.3% in proven cases, 99.3% in patients with moderate or severe disease, and 96.8% in those with galactomannan levels >1.8 ng/mL. Cross-reactivity was noted with other endemic mycoses. Conclusions: The MVista Histoplasma LFA meets the need for accurate rapid diagnosis of histoplasmosis in resource-limited countries, especially in patients with high disease burden, potentially reducing morbidity and mortality

AMPNet: Attention as Message Passing for Graph Neural Networks

Graph Neural Networks (GNNs) have emerged as a powerful representation learning framework for graph-structured data. A key limitation of conventional GNNs is their representation of each node with a singular feature vector, potentially overlooking intricate details about individual node features. Here, we propose an Attention-based Message-Passing layer for GNNs (AMPNet) that encodes individual features per node and models feature-level interactions through cross-node attention during message-passing steps. We demonstrate the abilities of AMPNet through extensive benchmarking on real-world biological systems such as fMRI brain activity recordings and spatial genomic data, improving over existing baselines by 20% on fMRI signal reconstruction, and further improving another 8% with positional embedding added. Finally, we validate the ability of AMPNet to uncover meaningful feature-level interactions through case studies on biological systems. We anticipate that our architecture will be highly applicable to graph-structured data where node entities encompass rich feature-level information.Comment: 16 pages (12 + 4 pages appendix). 5 figures and 7 table

Early life stress and macaque annygdala hypertrophy: preliminary evidence for a role for the serotonin transporter gene

Background: Children exposed to early life stress (ELS) exhibit enlarged amygdala volume in comparison to controls. the primary goal of this study was to examine amygdala volumes in bonnet macaques subjected to maternal variable foraging demand (VFD) rearing, a well-established model of ELS. Preliminary analyses examined the interaction of ELS and the serotonin transporter gene on amygdala volume. Secondary analyses were conducted to examine the association between amygdala volume and other stress-related variables previously found to distinguish VFD and non-VFD reared animals.Methods: Twelve VFD-reared and nine normally reared monkeys completed MRI scans on a 3T system (mean age = 5.2 years).Results: Left amygdala volume was larger in VFD vs. control macaques. Larger amygdala volume was associated with: high cerebrospinal fluid concentrations of corticotropin releasing-factor (CRF) determined when the animals were in adolescence (mean age = 2.7 years); reduced fractional anisotropy (FA) of the anterior limb of the internal capsule (ALIC) during young adulthood (mean age = 5.2 years) and timid anxiety-like responses to an intruder during full adulthood (mean age = 8.4 years). Right amygdala volume varied inversely with left hippocampal neurogenesis assessed in late adulthood (mean age = 8.7 years). Exploratory analyses also showed a gene-by-environment effect, with VFD-reared macaques with a single short allele of the serotonin transporter gene exhibiting larger amygdala volume compared to VFD-reared subjects with only the long allele and normally reared controls.Conclusion: These data suggest that the left amygdala exhibits hypertrophy after ELS, particularly in association with the serotonin transporter gene, and that amygdala volume variation occurs in concert with other key stress-related behavioral and neurobiological parameters observed across the lifecycle. Future research is required to understand the mechanisms underlying these diverse and persistent changes associated with ELS and amygdala volume.National Institute for Mental HealthNIMHNARSAD Mid-investigator AwardSuny Downstate Med Ctr, Dept Psychiat & Behav Sci, Brooklyn, NY 11203 USAUniversidade Federal de São Paulo, Dept Psiquiatria, São Paulo, BrazilMt Sinai Sch Med, Dept Psychiat, New York, NY USAMt Sinai Sch Med, Dept Neurosci, New York, NY USAMt Sinai Sch Med, Dept Radiol, New York, NY USANew York State Psychiat Inst & Hosp, New York, NY 10032 USAMichael E Debakey VA Med Ctr, Mental Hlth Care Line, Houston, TX USABaylor Coll Med, Menninger Dept Psychiat & Behav Sci, Houston, TX 77030 USAYale Univ, Sch Med, Dept Psychiat, New Haven, CT USANatl Ctr PTSD, Clin Neurosci Div, West Haven, CT USANew York State Psychiat Inst & Hosp, Dept Mol Imaging & Neuropathol, New York, NY 10032 USAColumbia Univ, Coll Phys & Surg, Dept Psychiat, New York, NY USAColumbia Univ, Coll Phys & Surg, Dept Pathol & Cell Biol, New York, NY USAComprehensive NeuroSci Corp, Westchester, NY USAUniv Miami Hlth Sytems, Dept Psychiat & Behav Sci, Miami, FL USAEmory Univ, Sch Med, Dept Psychiat & Behav Sci, Emory, GA USAUniversidade Federal de São Paulo, Dept Psiquiatria, São Paulo, BrazilNational Institute for Mental Health: R01MH65519-01National Institute for Mental Health: R01MH098073NIMH: R21MH066748NIMH: R01MH59990AWeb of Scienc

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects