Great Heterogeneity Research Articles

Temporal sequence of incident mild cognitive impairment, incident parkinsonism, and risk of death in unimpaired community-dwelling older adults.

Mild cognitive impairment (MCI) and parkinsonism affect many older adults. The objective of this study was to determine the sequence of their occurrence and associated risk of death. 1,255 community-dwelling unimpaired participants from two epidemiological cohorts were examined annually. MCI was based on neuropsychological testing, and parkinsonism was based on the motor portion of the modified Unified Parkinson's Disease Rating Scale. A multi-state Cox proportional hazards model simultaneously examined incidences of MCI, parkinsonism, and death. Average age at baseline was 76.5 years (SD = 7.2) and 73% were female. Incident MCI occurred almost as commonly as incident parkinsonism, yet compared to no impairment, risk of death was higher for MCI (HR = 1.82, 95%CI=1.34, 2.47), but it was not different for parkinsonism (HR = 1.29; 95%CI = 0.95, 1.75). Risk of death for participants with incident MCI who progressed to parkinsonism (40%) was not significantly different from those with MCI alone (HR = 1.25, 95%CI = 0.93, 1.69). However, risk of death for participants with incident parkinsonism who progressed to MCI (51%) was significantly higher than those who did not progress (HR = 1.67, 95%CI = 1.27, 2.18), indicating that risk of death is highest with incidence of MCI. The varied patterns of sequential occurrence of cognitive and motor impairment and associated risk of death suggests much greater heterogeneity than previously recognized. Further work is needed to determine the biology underlying the temporal evolution of these phenotypes, and if identification of the various subtypes improves risk stratification.

Utility of learning health systems in radiation oncology.

413 Background: Current health information systems lack a robust framework for longitudinal integration of internal experiences and external evidence into existing workflows. The result is labor intensive, error-prone and fragmented systems plagued with process gaps. Learning health systems (LHS) can be a potential solution to address these gaps. We created and implemented a novel LHS framework in radiation oncology (RO). We hypothesize that this framework can be leveraged to identify and implement opportunities for improvement using a patient-oriented endpoint of time from radiation simulation to treatment start (RSTS). Methods: An RO-LHS was developed through a collaboration between an academic, multi-facility radiation oncology department and an industry partner (Medlever). The end-to-end clinical workflow was embedded into the Medlever platform following an interdisciplinary, iterative analysis with representatives from key teams (clerical, finance and clinical). A novel nomenclature was created to label standardized, customizable templates, which choreograph logic-driven tasks that cover all sub-steps of RSTS. The primary endpoint of RSTS was compared pre- and post-implementation, stratified by key variables, such as facility, staff member, and radiation treatment modality. Results: The iterative workflow analysis identified >700 variables and decision points necessary for >200 cancer and benign conditions routinely managed in RO. >450 treatment protocols were templated.180 logic-driven tasks were created and linked to key parameters, resulting in a choregraphed precision workflow for each patient. Using the first iteration of the build, a total of 512 patients were managed during a 50-day period (03/01/2024-04/20/2024) and were compared to 2875 patients treated prior to implementation. Post-implementation, RSTS was shortened by 36.4% (p<0.001). We identified significant differences in RSTS by radiation modalities (protons vs all others), across facilities, and by providers (p<0.01 for all). Analysis of fractional domain of RSTS, 56% of the time was driven by physician-directed tasks, while 44% was comprised of physics and dosimetry-driven work. Physician-directed tasks had the greatest heterogeneity in time to completion. The biggest variation was noted for the contouring completion task. Significant differences were identified by provider (p<0.001) in nearly each step of the process, including steps not directly tied to physician’s work. Conclusions: Through an inter-disciplinary implementation of the first iteration of a LHS in our RO department, we have significantly shortened RSTS. The implementation and analysis has also enabled us to better understand underlying heterogeneities and identify further opportunities for optimization of RSTS. An LHS framework provides a generalizable solution that could be adapted in other RO clinics.

Comparative characteristics of the lipidome of Cycas revoluta and C. rumphii (Cycadaceae)

A targeted lipidomics analysis of four classes of membrane glycerolipids was carried out in two species of Cycadaceae from the genus Cycas – C. revoluta and C. rumphii. The analysis of the molecular diversity of the main phospholipids, which are the components of extra-chloroplast membranes, has revealed archaic features, including a high level of molecular species containing C18:1 fatty acids (typical of Ginkgo biloba), increased relative content of molecular species with odd fatty acids C17:0 and C19:0 (typical of non-seed plants). At the same time, the analysis of the molecular diversity of the glycolipids which are the components of chloroplast membranes, did not find significant differences from most seed plants, which indicates a higher conservation of lipids of a photosynthetic apparatus. The identified features of the molecular composition of glycerolipids of two species of Cycas indicate the prospectiveness of using lipidomics for taxonomic and phylogenetic studies, with the data on the molecular composition of phosphatidylcholines, for which the greatest heterogeneity and species-specificity was demonstrated, deserving the most attention.

The diversity of soil-dwelling arthropods is significantly influenced by land use systems with tree cover in semiarid conditions

Seasonal changes in vegetation and climate exert significant influences on soil fauna in natural and agricultural ecosystems. Additionally, evidence indicates that interactions between different plant layers promote soil fauna diversity through the variety of resources available. The objective was to assess the edaphic fauna in traditional land use systems, agroforestry systems and natural vegetation, under the influence of rainfall seasonality and plant strata in the semiarid region of Brazil. For this purpose, six types of land use were selected: agroforestry; silvopastoral; slash and burn with intensive use without fallow; slash and burn with six years of fallow; slash and burn with nine years of fallow; and a system representing the natural vegetation of the Caatinga. Edaphic fauna was collected using pitfall traps in the dry and rainy seasons. A total of 43,363 individuals of the edaphic fauna were collected and grouped into taxa, determining abundance, diversity and functional groups. The results revealed higher abundance and diversity of edaphic fauna in the rainy season across all land use systems, but significantly higher numbers in systems with tree strata. The greater the abundance, richness and diversity of trees, the higher the diversity of edaphic fauna (Shannon Index - H: 0.7 < ‾H < 1) for the seasonal effect. Agroforestry systems were intermediate in the diversity of edaphic fauna (‾H < 0.8) compared to other systems. Systems with greater heterogeneity in tree and herbaceous strata were the ones that most increased the diversity and activity of functional groups of edaphic fauna (H < 0.8; 0.5 < r < 0.9). In semiarid conditions, more attention should be given to agricultural production systems with greater tree diversity and interaction between tree and herbaceous strata to conserve the biodiversity of edaphic fauna and improve the soil health.

Bi-Directional and Time-Lagged Associations between Engagement and Mental Health Symptoms in a Group Mindfulness-Based Mental Health Intervention.

There is a high need for accessible avenues for improving mental health among emerging adults, particularly on college campuses. Mindfulness-based intervention (MBI) is a promising avenue for reducing mental health symptoms, but initial discomforts associated with MBI may cause symptoms to fluctuate before decreasing, which presents a barrier to engagement with mindfulness on a daily basis. Consistent mindfulness practice is key for forming habits related to MBI, and engagement with mindfulness at home, including between intervention sessions, is an important predictor of mental health outcomes. Research suggests that mental health symptoms may serve as barriers to their own treatment. Thus, it is important to understand how mental health symptom levels impact adherence to treatment protocols. To improve understanding of symptom-specific barriers to treatment and engagement with mindfulness, the present study collected daily diary surveys about engagement with mindfulness and mental health symptoms from a sample of 62 adults recruited to participate in a six-week mindfulness intervention. We explored mental health symptoms as a predictor of engagement with MBI at the mean level and whether within-person variability in symptoms predicted same-day or time-lagged changes in engagement via mixed-effects associations. Using heterogeneous location scale models, we further explored whether erraticism in either mental health symptoms or engagement with mindfulness predicted the other and if outcomes of the mindfulness intervention were homogeneous among subjects. Results showed that bi-directional and time-lagged associations exist between symptoms and engagement, indicating that there is a nuanced temporal and reciprocal relationship between engagement with mindfulness and mental health symptoms. Daily within-person elevations in engagement with mindfulness were associated with concurrent improvements in mental health but prospective increases in mental health symptoms. We also found that higher engagement (over personal averages) was not consistently associated with improvements in mental health across the sample but was instead associated with greater heterogeneity in outcomes. We also found that increases in mental health symptoms (over personal averages), as well as higher average levels of mental health symptoms, were both associated with lower levels of engagement in the mindfulness treatment protocol.

Effect of porosity and pore heterogeneity on heat transfer performance of polyimide aerogels

The effects of porosity and pore distribution on the heat transfer performance of polyimide (PI) aerogel under natural convection were investigated through a combination of experimental and numerical simulations. The governing equations of heat transfer were analyzed in detail. A novel heterogeneity factor (η) was introduced to quantify internal pore distribution. PI aerogels exhibiting a range of porosities and heterogeneity factors were synthesized and characterized. The natural convection heat transfer coefficient of PI aerogels was measured experimentally, providing empirical data. A porous model was developed by integrating Voronoi technique with a two-scale generation method, allowing for comprehensive numerical simulations of heat transfer. The numerical results demonstrated strong concordance with the experimental data, validating the model’s accuracy. The results revealed that the heat transfer performance of the aerogels diminished markedly with increasing porosity when heterogeneity was held constant. Conversely, with fixed porosity, the heat transfer performance improved significantly with greater heterogeneity. Numerical simulations further enabled the visualization of internal temperature and flow fields, elucidating that the effect of porosity and heterogeneity on natural convection heat transfer performance is predominantly driven by variations in internal permeability.

Evaluation of five nutritional scores as predictors of postoperative outcome following pancreatic resection: A prospective, single-center study

Background and aimsPatients undergoing pancreatic resection are commonly malnourished. It is still unclear whether nutritional scores reliably predict postoperative outcomes after pancreatic resection. This study evaluated whether five commonly used preoperative nutritional screening scores predicted severe complications and length of stay. MethodsPatients scheduled for pancreatic resection (pancreatoduodenectomy, distal and total pancreatectomy) at a national referral center for pancreatic surgery from September 2022 to June 2023 were prospectively screened for malnutrition with MNA, MUST, SGA, SNAQ, and NRS2002 scores. Postoperative complications were classified using the Clavien-Dindo classification. #NCT05608538. ResultsThree hundred patients were enrolled, including 168 pancreatoduodenectomies (56%), 102 distal pancreatectomies (34%), and 30 total pancreatectomies (10%). Final pathology revealed malignancy in 203 cases (67.7%). When applying the scores, the proportion of patients malnourished or at risk of malnutrition ranged from 21.7% for SGA to 79.3% for NRS2002. After adjusting for selected confounders, only an MNA <17 was associated with severe postoperative complications (OR 8.39, 95%CI[1.95 – 32.31], p=0.01). MNA, SGA, and SNAQ predicted the length of stay (all p<0.01), while MNA and SGA also correlated with a higher probability of having a greater heterogeneity in the length of stay (p=0.04 and 0.002, respectively). DiscussionWe promote using MNA to detect malnourished patients at risk of severe postoperative complications and longer hospitalization after pancreatic surgery. SGA and SNAQ may also have value in predicting patients who will be hospitalized longer. More prospective studies will be needed to corroborate these findings.

The cereal network: a baseline approach to current configurations of trade communities

This paper attempts to provide insights into the current network configurations of the food-trade system and to study the short-term effects of one of the ongoing and lasting global crises, the Ukraine War, on the link intensity. Towards this end, this analysis (1) reveals the pattern of countries’ network positions in two most traded subcategories of the cereal network: wheat and meslin, and maize or corn, and (2) discusses the characteristics of the global cereal networks over the 2021–2022 period. The results highlight several features of the trade networks: (1) the distribution of cereal trade is highly concentrated, with considerable dependency on a small number of exporters and a low import diversification, making the system rigid and prone to shocks; (2) a central role of several key developed countries that leave many developing countries outside the centre of the networks; (3) a high network heterogeneity which confirms the propensity to have hub nodes. Particular indicators show that the highest level of interconnectivity is specific to the cereals’ export network, the densest networks are the maize or corn ones, and the greatest heterogeneity appears for the cereals export network.

Mapping the strain-stiffening behavior of the lung and lung cancer at microscale resolution using the crystal ribcage.

Lung diseases such as cancer substantially alter the mechanical properties of the organ with direct impact on the development, progression, diagnosis, and treatment response of diseases. Despite significant interest in the lung's material properties, measuring the stiffness of intact lungs at sub-alveolar resolution has not been possible. Recently, we developed the crystal ribcage to image functioning lungs at optical resolution while controlling physiological parameters such as air pressure. Here, we introduce a data-driven, multiscale network model that takes images of the lung at different distending pressures, acquired via the crystal ribcage, and produces corresponding absolute stiffness maps. Following validation, we report absolute stiffness maps of the functioning lung at microscale resolution in health and disease. For representative images of a healthy lung and a lung with primary cancer, we find that while the lung exhibits significant stiffness heterogeneity at the microscale, primary tumors introduce even greater heterogeneity into the lung's microenvironment. Additionally, we observe that while the healthy alveoli exhibit strain-stiffening of ∼1.75 times, the tumor's stiffness increases by a factor of six across the range of measured transpulmonary pressures. While the tumor stiffness is 1.4 times the lung stiffness at a transpulmonary pressure of three cmH2O, the tumor's mean stiffness is nearly five times greater than that of the surrounding tissue at a transpulmonary pressure of 18 cmH2O. Finally, we report that the variance in both strain and stiffness increases with transpulmonary pressure in both the healthy and cancerous lungs. Our new method allows quantitative assessment of disease-induced stiffness changes in the alveoli with implications for mechanotransduction.

Cross-sectional and spatial panel data analysis of territorial economic cohesion in the European Union regions based on convergence approach: From 2 to 8 per cent?

From an economic, political and social standpoint, one of the most evident and visible features of today's European Union as a supranational regional organization is its heterogeneity, where disparity seems to be the common denominator. This leads to the interest for measuring the territorial economic cohesion of the EU. From an eminently economic perspective, and working with the GDP per capita of the EU NUTS-2 regions for the period 2003–2021, this paper aims to provide evidence of a lack of territorial economic cohesion through a beta and sigma convergence methodology by applying cross-sectional and spatial panel data analysis.The findings show that the speed of convergence depends mainly on the level of economic development, its cycles and the heterogeneity of the, which implies conditional convergence. Less developed regions show higher convergence speeds, which are also accentuated during recession periods. Greater heterogeneity among the regions also increases the convergence speed, while accentuating in the less developed regions. In general terms, the results reveal convergence speeds of the entire NUTS-2 regions between 7 and 11 per cent (much higher than 2 per cent under absolute convergence). Likewise, when considering spatial dependence, a reduction in convergence speeds between approximately 3 and 8 per cent is detected. Finally, the 29 vulnerable regions have been identified, with economic development and growth below the EU average mean, emphasizing the need to take the concerns of territorial economic cohesion into account.

Exploring Heterogeneity in Cost-Effectiveness Using Machine Learning Methods: A Case Study Using the FIRST-ABC Trial.

The aim of this study was to explore heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) in children following extubation. Using data from the FIRST-line support for Assistance in Breathing in Children (FIRST-ABC) trial, we explore heterogeneity at the individual and subgroup levels using a causal forest approach, alongside a seemingly unrelated regression (SUR) approach for comparison. FIRST-ABC is a noninferiority randomized controlled trial (ISRCTN60048867) including children in UK paediatric intensive care units, which compared HFNC with CPAP as the first-line mode of noninvasive respiratory support. In the step-down FIRST-ABC, 600 children clinically assessed to require noninvasive respiratory support were randomly assigned to HFNC and CPAP groups with 1:1 treatment allocation ratio. In this analysis, 118 patients were excluded because they did not consent to accessing their medical records, did not consent to follow-up questionnaire or did not receive respiratory support. The primary outcome of this study is the incremental net monetary benefit (INB) of HFNC compared with CPAP using a willingness-to-pay threshold of £20,000 per QALY gain. INB is calculated based on total costs and quality adjusted life years (QALYs) at 6 months. The findings suggest modest heterogeneity in cost-effectiveness of HFNC compared with CPAP at the subgroup level, while greater heterogeneity is detected at the individual level. The estimated overall INB of HFNC is smaller than the INB for patients with better baseline status suggesting that HFNC can be more cost-effective among less severely ill patients.

Detecting and quantifying heterogeneity in susceptibility using contact tracing data.

The presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which are typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed these data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone are sufficient to detect and quantify heterogeneity in susceptibility.

Structural, Functional, and Electrical Remodeling of the Atria With Reduced Cardiorespiratory Fitness: Implications for AF

BackgroundReduced cardiorespiratory fitness (CRF) is an independent risk factor for the progression of atrial fibrillation (AF). We hypothesized that reduced CRF is associated with structural, functional, and electrical remodeling of the left atrium. ObjectivesThis study sought to correlate objectively assessed CRF with functional and electrical left atrial (LA) parameters using invasive and noninvasive assessments. MethodsConsecutive patients with symptomatic AF undergoing catheter ablation were recruited. CRF was objectively quantified pre-ablation by using cardiopulmonary exercise testing. Using peak oxygen consumption, participants were classified as preserved CRF (>20 mL/kg/min) or reduced CRF (<20 mL/kg/min). LA stiffness was assessed invasively with hemodynamic monitoring and imaging during high-volume LA saline infusion. LA stiffness was calculated as ΔLA diameter/ΔLA pressure over the course of the infusion. LA function was assessed with echocardiographic measures of LA emptying fraction and LA strain. Electrical remodeling was assessed by using high-density electroanatomical maps for LA voltage and conduction. ResultsIn total, 100 participants were recruited; 43 had reduced CRF and 57 had preserved CRF. Patients with reduced CRF displayed elevated LA stiffness (P = 0.004), reduced LA emptying fraction (P = 0.006), and reduced LA reservoir strain (P < 0.001). Reduced CRF was also associated with reduced LA voltage (P = 0.039) with greater heterogeneity (P = 0.027) and conduction slowing (P = 0.04) with greater conduction heterogeneity (P = 0.02). On multivariable analysis, peak oxygen consumption was independently associated with LA stiffness (P = 0.003) and LA conduction velocities (P = 0.04). ConclusionsReduced CRF in patients with AF is independently associated with worse LA disease involving functional and electrical changes. Improving CRF may be a target for restoring LA function in AF.

Age at death during the Covid-19 lockdown in French metropolitan regions: a non parametric quantile regression approach

BackgroundLockdowns have been implemented to limit the number of hospitalisations and deaths during the first wave of 2019 coronavirus disease. These measures may have affected differently death characteristics, such age and sex. France was one of the hardest hit countries in Europe with a decreasing east–west gradient in excess mortality. This study aimed at describing the evolution of age at death quantiles during the lockdown in spring 2020 (17 March—11 May 2020) in the French metropolitan regions focusing on 3 representatives of the epidemic variations in the country: Bretagne, Ile-de-France (IDF) and Bourgogne-Franche-Comté (BFC).MethodsData were extracted from the French public mortality database from 1 January 2011 to 31 August 2020. The age distribution of mortality observed during the lockdown period (based on each decile, plus quantiles 1, 5, 95 and 99) was compared with the expected one using Bayesian non-parametric quantile regression.ResultsDuring the lockdown, 5457, 5917 and 22 346 deaths were reported in Bretagne, BFC and IDF, respectively. An excess mortality from + 3% in Bretagne to + 102% in IDF was observed during lockdown compared to the 3 previous years. Lockdown led to an important increase in the first quantiles of age at death, irrespective of the region, while the increase was more gradual for older age groups. It corresponded to fewer young people, mainly males, dying during the lockdown, with an increase in the age at death in the first quantile of about 7 years across regions. In females, a less significant shift in the first quantiles and a greater heterogeneity between regions were shown. A greater shift was observed in eastern region and IDF, which may also represent excess mortality among the elderly.ConclusionsThis study focused on the innovative outcome of the age distribution at death. It shows the first quantiles of age at death increased differentially according to sex during the lockdown period, overall shift seems to depend on prior epidemic intensity before lockdown and complements studies on excess mortality during lockdowns.

Triggering Chinese lecturers' intrinsic work motivation by value-based leadership and growth mindset: Generation difference by using multigroup analysis.

This cross-sectional study investigated the effects of value-based leadership and growth mindset on the intrinsic work motivation of Chinese lecturers. In addition, this study used age as a categorical moderator to investigate generational differences between the effects of Millennials and their predecessors. A sample of 518 lecturers from various Chinese universities was used to collect data, and SEM-PLS was used to analyse the data. The results showed that value-based leadership and growth mindset had a significant positive impact on both younger and older lecturers' intrinsic work motivation, with the effect of value-based leadership on younger lecturers' intrinsic motivation being significantly stronger than on older lecturers' intrinsic motivation, whereas the effect of growth mindset on intrinsic work motivation did not differ significantly between the younger and older groups. This study contributes to the existing research literature by contrasting the value-based leadership and growth mindset in relation to lecturers' intrinsic work motivation across younger and older groups in Chinese higher education settings, where greater heterogeneity between age groups was identified. The findings also provided university administrators with recommendations for boosting the intrinsic work motivation of lecturers, influencing future education policy.

Is the insular coastal tourism of western Greece at risk due to climate induced sea level rise?

Coastal environments and, especially, beach zones are among the most common areas for tourism activity, comprising valuable economic resources. Beach zones are highly dynamic environments, recognized as highly vulnerable to climate change coastal ecosystems because of, amongst other, extreme events and sea-level rise. It is considerably important for beach tourism management the development of proper adaptation strategies. The scope of this study is to provide an assessment of the potential climate-related risk on touristic beaches of the Ionian Islands (Greece) by applying a three-step risk assessment methodology, following the impact chain conceptual framework. More specifically, the methodology integrates: (i) beach hazard as an expression of beach retreat calculation due to sea level rise to the extreme SSP5-8.5 scenario for 2050, (ii) beach exposure with regard to tourism economic losses according to the extent of beach touristic exploitation, and (iii) beach vulnerability with regard to both beach capacity considering its morphological characteristics and sensitivity considering the adverse impact of artificial structures and human development in the area. The results indicate a great heterogeneity in risk, with more than half beaches being at high or very high risk under the highest emissions scenario.

The vegetation–topography heterogeneity coupling in the Loess Plateau, China

As a result of adaptation to the environment, the great environmental spatial heterogeneity leads to the high spatial heterogeneity of vegetation status. This coupling may be more apparent in water-limited drylands, where topography is the main determinant of small-scale variation in water availability and energy. Metrics describing this coupling may contribute to the detection of the extension of vegetation reshaped by human intervention and other driven forces. In this study, the heterogeneity index of coupling (HIC) was developed to indicate the coupling between spatial heterogeneity of vegetation status (Hv) and the spatial heterogeneity of topography (HT) in the Loess Plateau in northern China. The 16-day composed MODIS normalized vegetation index (NDVI) with a resolution of 250 m and SRTM DEM were employed to quantify the heterogeneity of vegetation status and the topographical heterogeneity. The results show that HIC varies among geomorphic zones, land cover types, and land cover change categories. Among all land cover types, HIC of sandy areas was the largest, followed by the HIC of the forest, shrub, farmland, and grassland. Among geomorphic zones, the highest HIC value appeared in plains with dense residential areas, followed by sandy land that is frequently reshaped by wind, rocky mountainous areas, hilly and gully loess plateaus, and loess tableland. It was revealed that the alternation of vegetation by human activities and natural disturbances shaped greater HIC. Results of this study approved the effectiveness of the HIC in reflecting the coupling of the vegetation status with topography at regional scale.

Large-scale in-silico analysis of CSF dynamics within the subarachnoid space of the optic nerve

BackgroundImpaired cerebrospinal fluid (CSF) dynamics is involved in the pathophysiology of neurodegenerative diseases of the central nervous system and the optic nerve (ON), including Alzheimer’s and Parkinson’s disease, as well as frontotemporal dementia. The smallness and intricate architecture of the optic nerve subarachnoid space (ONSAS) hamper accurate measurements of CSF dynamics in this space, and effects of geometrical changes due to pathophysiological processes remain unclear. The aim of this study is to investigate CSF dynamics and its response to structural alterations of the ONSAS, from first principles, with supercomputers.MethodsLarge-scale in-silico investigations were performed by means of computational fluid dynamics (CFD) analysis. High-order direct numerical simulations (DNS) have been carried out on ONSAS geometry at a resolution of 1.625 μm/pixel. Morphological changes on the ONSAS microstructure have been examined in relation to CSF pressure gradient (CSFPG) and wall strain rate, a quantitative proxy for mass transfer of solutes.ResultsA physiological flow speed of 0.5 mm/s is achieved by imposing a hydrostatic pressure gradient of 0.37–0.67 Pa/mm across the ONSAS structure. At constant volumetric rate, the relationship between pressure gradient and CSF-accessible volume is well captured by an exponential curve. The ONSAS microstructure exhibits superior mass transfer compared to other geometrical shapes considered. An ONSAS featuring no microstructure displays a threefold smaller surface area, and a 17-fold decrease in mass transfer rate. Moreover, ONSAS trabeculae seem key players in mass transfer.ConclusionsThe present analysis suggests that a pressure drop of 0.1–0.2 mmHg over 4 cm is sufficient to steadily drive CSF through the entire subarachnoid space. Despite low hydraulic resistance, great heterogeneity in flow speeds puts certain areas of the ONSAS at risk of stagnation. Alterations of the ONSAS architecture aimed at mimicking pathological conditions highlight direct relationships between CSF volume and drainage capability. Compared to the morphological manipulations considered herein, the original ONSAS architecture seems optimized towards providing maximum mass transfer across a wide range of pressure gradients and volumetric rates, with emphasis on trabecular structures. This might shed light on pathophysiological processes leading to damage associated with insufficient CSF flow in patients with optic nerve compartment syndrome.

Prévalence des troubles psychiatriques en population carcérale française : une revue systématique de la littérature

IntroductionThe prevalence of psychiatric disorders among prisoners remains a major public health issue worldwide. In France, despite the increasing number of persons who are incarcerated (+30% between 1992 and 2002 with a 120% prison overcrowding), and a historical concern about the mental health of persons in detention and its management, no systematic review has been published on this subject. The aim of this article is to present the results of a systematic review of the literature on the prevalence of psychiatric disorders in French prisons. MethodThe reporting of this systematic review conforms to the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) checklist. We searched the PubMed and Web of Science databases. We used combinations of keywords relating to prison (prison*, jail*, inmate*), to psychiatry (“mental health”, psychiatr*), and to France (France, French). This work was completed with a search through the digital libraries of the École des Hautes Études en Santé Publique (EHESP) and of the Système Universitaire de Documentation (Sudoc) to obtain data from academic works and the gray literature. References cited in studies included in this review were also examined. All references published up to September 2022, written in English or French, presenting the results of original quantitative studies on the prevalence of psychiatric disorders in correctional settings were included. Two researchers independently extracted data from included references according to a pre-established protocol. ResultsAmong 501 records identified, a total of 35 papers based on 24 epidemiological studies met the eligibility criteria for inclusion in this review: 16 were cross-sectional, 7 retrospective and 1 both cross-sectional and retrospective. All papers were published between 1999 and 2022. We found one European study, 5 international studies, 18 regional or local studies. Of these, 21 studies had all-male or mixed gender samples (but when the sample was mixed gender, it was always at least 92% male). Almost half of the studies (n=11) involved a small sample of fewer than 500 persons. Half of the studies involved a sample of recently incarcerated persons: 6 involved a random sample of persons in detention, and 1 involved a sample of people incarcerated for more than 5 years. The last 5 studies focused on persons aged over 50 years and incarcerated for more than one year (n=1), incarcerated for sexual offences (n=2), placed in disciplinary cells (n=1) or in a special wing for radicalized or suspected radicalized individuals (n=1). Nine studies used standardized and validated diagnostic tools. According to the 4 studies involving representative samples and using standardized and validated diagnostic tools, the prevalence of the following psychiatric disorders was: 29.4–44.4% for anxiety disorders, 5–14.2% for PTSD, 28–31.2% for mood disorders, 6.9–17% for psychotic disorders, 32% for personality disorders and 11% for ADHD. ConclusionThis systematic review of the literature highlights the high prevalence of psychiatric disorders in French prisons. The data collected are in line with international studies. The great methodological heterogeneity of the papers included in this review calls for further rigorous research to better understand the rates of mental disorders in French prisons and to explore their determinants.

Chemokine CCL21 determines immunotherapy response in hepatocellular carcinoma by affecting neutrophil polarization

BackgroundThe efficacy of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) is poor and great heterogeneity among individuals. Chemokines are highly correlated with tumor immune response. Here, we aimed to identify an effective chemokine for predicting the efficacy of immunotherapy in HCC.MethodsChemokine C‐C motif ligand 21 (CCL21) was screened by transcriptomic analysis in tumor tissues from HCC patients with different responses to ICIs. The least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive nomogram. Neutrophils in vitro and HCC subcutaneous tumor model in vivo were applied to explore the role of CCL21 on the tumor microenvironment (TME) of HCC.ResultsTranscriptome analysis showed that CCL21 level was much higher in HCC patients with response to immunotherapy. The predictive nomogram was constructed and validated as a classifier. CCL21 could inhibit N2 neutrophil polarization by suppressing the activation of nuclear factor kappa B (NF-κB) pathway. In addition, CCL21 enhanced the therapeutic efficacy of ICIs.ConclusionCCL21 may serve as a predictive biomarker for immunotherapy response in HCC patients. High levels of CCL21 in TME inhibit immunosuppressive polarization of neutrophils. CCL21 in combination with ICIs may offer a novel therapeutic strategy for HCC.