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Protocol for a process and implementation evaluation of the SMARThealth pregnancy hybrid type 2 cluster randomised controlled trial
No full textBackground:
This protocol outlines the process and implementation evaluation of the SMARThealth Pregnancy (SHP) pragmatic, type 2 hybrid cluster randomised trial conducted in two states in India (Haryana/Telangana). The SHP trial aims to improve the community-level identification, diagnosis, referral and management of women with anaemia, diabetes and hypertension during pregnancy and in the year after birth.
Objectives:
The process and implementation evaluation aims to understand how, why and for whom the SHP
intervention may be effective (or not). It aims to identify contextual factors, barriers and facilitators relevant to the implementation of the intervention, and understand mechanisms and strategies employed during its implementation.
Design:
Process evaluation.
Method:
A mixed methods evaluation drawing from realist evaluation, Normalisation process theory, the Medical Research Council framework, RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) framework, and Proctor’s typology will be employed for understanding the implementation process. The evaluation will involve focus group discussions and semi-structured interviews with healthcare providers (Accredited Social Health Activist, primary care doctors, and Auxiliary Nurse Midwife), women and field staff. Quantitative process data describing reach, fidelity,dose, and adoption of intervention will be collected. Observations of trial set up and implementation will be conducted. Both qualitative and quantitative data will be analysed iteratively before the effectiveness outcomes of the SHP trial are available, and will subsequently be triangulated with the
trial primary outcome evaluation data.
Discussion
The findings from this process evaluation will provide an understanding of how the intervention works in practice, its potential to detect and manage anaemia, diabetes and hypertension during pregnancy and in the year after birth, and its scalability as an integrated model for the management of NCDs in pregnancy/postnatal care
The Intelligence Capital Manifesto: how enterprises can win in the intelligence economy
No full textThis paper develops a unified theoretical and empirical framework for understanding the rise of Intelligence Capital as a new dominant factor of production: institutionalized, process-owning human+AI systems that learn, retain memory, and compound in economic value.
We argue that recent macroeconomic anomalies, including sustained output growth with weak employment creation, rising productivity without proportional hiring, and increased capital concentration, reflect a structural transition rather than cyclical fluctuations. Using cross-national labor and productivity data, we document a “labor inversion” in which output increasingly flows through embedded intelligence systems prior to labor-market absorption, generating persistent “phantom jobs.”
At the microeconomic level, we reinterpret the firm as a learning-and-compounding engine rather than a transaction-cost minimizer, modeling enterprises as portfolios of Intelligence Capital Generators that internalize knowledge, capture feedback, and exhibit power-law return dynamics.
We introduce the Intelligence Capital Yield Function to formalize how exploration, failure, and institutional learning are converted into scalable economic advantage. The analysis shows that high experimental failure rates and valuation asymmetries are endogenous features of Intelligence Capital formation rather than indicators of misallocation.
Finally, we identify organizational and behavioral constraints that limit compounding and propose governance mechanisms that align managerial incentives with long-run learning yield. The findings contribute to theories of the firm, endogenous growth, and technological change by demonstrating how intelligence-based capital reshapes productivity, employment, and competitive dynamics in advanced economies
Safety and effectiveness of rivaroxaban thromboprophylaxis in ACTH-dependent cushing syndrome
No full textContext
ACTH-dependent Cushing syndrome (CS) is associated with a markedly increased risk of venous thromboembolism (VTE), yet thromboprophylaxis strategies remain inconsistent across clinical practice. In 2019, our center introduced routine oral
rivaroxaban prophylaxis (10 mg once daily) for all patients with ACTH-dependent CS.
Objective
To evaluate the safety and effectiveness of routine rivaroxaban prophylaxis in ACTH dependent CS.
Methods
We retrospectively reviewed 70 adults with ACTH-dependent CS managed between
2012–2025 (29 pre-2019; 41 post-2019) to compare VTE incidence before and after
the introduction of rivaroxaban.
Results
There were no differences in baseline characteristics between the two groups. Cushing
disease (ie secondary to a pituitary corticotroph adenoma) was the most common
subtype (26/29 pre-2019 and 34/41 post-2019). Among patients without routine prophylaxis (pre-2019), four patients (13.8%) developed six VTE events, occurring
both pre- and postoperatively. In contrast, no new or recurrent VTE events occurred in the post-2019 cohort receiving rivaroxaban prophylaxis (n=39), although five patients had prior VTE before endocrine assessment for hypercortisolism and rivaroxaban initiation. No major or minor bleeding complications were observed. Haematological parameters remained stable, and all patients completed the prescribed prophylaxis
course (median duration: 7.9 months).
Conclusions
In our cohort, VTE incidence was 13.8% without prophylaxis and did not occur after the introduction of routine rivaroxaban. Prophylactic oral rivaroxaban in ACTH-dependent CS was safe and effective in preventing new, recurrent, perioperative, and
postoperative VTE events, supporting its early initiation at diagnosis and continuation through the peri-and postoperative period
Prevalence of gestational diabetes mellitus in Sub-Saharan Africa: a systematic review and meta-analysis
No full textBackground
Gestational diabetes mellitus (GDM) is a significant cause of adverse perinatal outcomes and major risk factor for type 2 diabetes in mother and child. Although global prevalence is estimated at 14%, the burden in sub-Saharan Africa remains unclear due to limited data and variable diagnostic protocols. This study aimed to generate a robust estimate of GDM prevalence in sub-Saharan Africa using methodologically comparable studies, and to assess subregional variation.
Methods
We systematically searched Embase, MEDLINE, CINAHL, Global Health, African Journals Online, and African Index Medicus from January 1990 to March 2025 for observational studies of pregnant women in sub-Saharan Africa screened for GDM at ≥24 weeks’ gestation using an oral glucose tolerance test and internationally recognised criteria. Studies using inconsistent, unclear or incomplete diagnostic protocols or self-reported data were excluded. Quality was assessed using the Joanna Briggs Institute checklist. Prevalence estimates were pooled using random-effects meta-analysis of Freeman–Tukey–transformed proportions. Subgroup analyses were conducted by subregion, and mixed-effects meta-regression examined study-level moderators.
Findings
Fifty-nine studies met the inclusion criteria, of which 49 were selected for meta-analysis based on use of comparable diagnostic criteria. Studies represented 16 countries and involved 27 540 participants. The pooled GDM prevalence was 14·0% (95% CI 11·6–16·5; prediction interval 1·9–34·3) with substantial heterogeneity (I² = 97·1%). Prevalence varied across subregions: Southern Africa 10·2%, Eastern Africa 13·9%, Western Africa 15·1%, and Central Africa 18·0%. Meta-regression showed that small studies (<300 participants), studies using point-of-care testing, and studies conducted before 2016 reported higher prevalence. Subregional differences persisted after adjustment.
Interpretation
When comparable diagnostic protocols are applied, GDM prevalence in sub-Saharan Africa matches the global average, challenging perceptions of a lower regional burden. Subregional variability highlights the need for locally representative data. Standardised diagnostic criteria for epidemiological studies would improve comparability and inform targeted public health interventions
Cost of diabetes and hypertension care among patients in rural Bangladesh: a cross-sectional study
No full textBackground
Hypertension and diabetes impose significant health and economic burdens in low-and middle-income countries like Bangladesh. This study aimed to estimate both direct and indirect costs associated with hypertension and diabetes care in Dinajpur, a rural district of Bangladesh, and identify factors influencing these costs.
Methods
This cross-sectional study used baseline data from a community survey conducted as part of an ongoing implementation research project. A multistage cluster sampling approach was used to randomly select adults aged 40 years and above from 45 wards across three subdistricts of Dinajpur. The analysis included 832 individuals who reported being on medication for hypertension (n = 635) and/or diabetes (n = 335). Data were collected through structured questionnaires, capturing direct (medical and non-medical) and indirect costs (productivity losses). Descriptive statistics, Wilcoxon rank-sum, and Kruskal-Wallis tests were used for univariate analyses. Multivariate linear regression models with log-transformed cost data were used to identify cost determinants.
Results
The average monthly total cost per patient was BDT 1,308 (USD 10.8) for hypertension and BDT 2,064 (USD 17.1) for diabetes. For both conditions, direct medical costs accounted for around 80% of total costs (60% for medicines), direct non-medical costs around 11% (mostly food and travel), and indirect costs approximately 9%. Direct costs were lower at public facilities compared to private dispensaries (Hypertension: GMR 0.46, 95% CI 0.33–0.64; Diabetes: GMR 0.15, 95% CI 0.10–0.24), while higher costs were observed for private clinics and NGO facilities. Level of education was associated with higher direct costs, particularly among patients with primary or secondary or higher education. Comorbidities were also associated with higher direct costs: in hypertension, cardiovascular disease (GMR 1.78, 95% CI 1.35–2.35) and high cholesterol (GMR 2.16, 95% CI 1.49–3.14) increased direct costs, with similar associations for diabetes costs. Indirect costs, reflecting productivity losses, were higher for private clinics, public facilities, and NGO facilities compared to private dispensaries.
Conclusions
In the sample taken from a rural region from Bangladesh, hypertension and diabetes care entails a considerable financial burden, driven largely by medicine costs and reliance on private healthcare providers. Improved access to essential services and financial protection strategies are needed to reduce out-of-pocket expenditures.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request
C-type natriuretic peptide preserves vascular and cardiac function in sepsis
No full textBACKGROUND:
Sepsis is a life-threatening condition and a major cause of mortality in intensive care units worldwide, a clear unmet medical need. CNP (C-type natriuretic peptide) regulates inflammation and cardiovascular homeostasis, but its involvement in sepsis pathogenesis is not fully elucidated. This study investigated the intrinsic role of CNP, and therapeutic potential of the peptide, in offsetting the pathogenesis of sepsis.
METHODS:
Plasma concentrations of CNP, and its N-terminal cleavage product NT-proCNP (N-terminal pro-CNP), were measured in sepsis patients. Cardiac function, vascular hemodynamics, endothelial integrity, and biomarkers of inflammation were analyzed in wild-type, endothelium-restricted (ecCNP−/−), or cardiomyocyte-restricted (cmCNP−/−) CNP knockout animals, or global NPR (natriuretic peptide receptor)-C−/− deficient mice, in etiologically distinct models of sepsis. CNP (0.2 mg/kg per d) was infused to rescue any adverse phenotype and probe therapeutic potential.
RESULTS:
Circulating (NT-proCNP) increased in sepsis patients and was associated with reduced disease severity. ecCNP−/− mice exhibited an aggravated phenotype compared with wild-type mice in experimental sepsis, exemplified by impaired microcirculatory flow, edema, and increased expression of inflammatory biomarkers. In addition, cmCNP−/− animals showed overt cardiac dysfunction following lipopolysaccharide treatment. This worsened phenotype was mirrored in NPR-C−/− mice, implying that this cognate NPR subtype underpins the salutary actions of endogenous CNP. Pharmacological CNP administration improved microvascular perfusion, cardiac output, and inflammation in wild-type and ecCNP−/−, but not NPR-C−/−, mice.
CONCLUSIONS:
Endogenous CNP plays a protective role in sepsis by preserving microvascular perfusion, reducing inflammation, maintaining endothelial integrity, and sustaining cardiac function via NPR-C. Pharmacologically targeting CNP signaling warrants further evaluation as a potential therapeutic opportunity in sepsis
Microstructure evolution and sensitization of additively manufactured duplex stainless steel during aging heat treatments
No full textDuplex stainless steels (DSS) combine excellent mechanical and corrosion resistance properties. They are now increasingly fabricated by laser powder bed fusion (LPBF). A significant concern with DSS is sensitization, which is caused by the formation of deleterious precipitates during exposure to elevated temperatures. Yet, this behavior has never been systematically studied in additively manufactured DSS. Here, we investigate how the unique microstructure of LPBF-manufactured DSS affects the sensitization behavior by comparing hot-rolled, as-built, and solution-annealed LPBF specimens subjected to isothermal aging at 825 °C for 30 to 600 mins. Light optical and scanning electron microscopy, along with electron backscatter diffraction, reveal differences in the microstructural evolution, showing initially slower σ and χ precipitation in LPBF samples due to a more coherent ferrite/austenite boundary structure. Nevertheless, double-loop electrochemical potentiokinetic reactivation testing reveals that the sensitized, as-printed LPBF microstructure exhibits a comparatively faster deterioration of its corrosion resistance. This is attributed to the formation of low-Cr containing austenite during aging at 825 °C. Atom probe tomography corroborates this finding and reveals additional Cr-depletion adjacent to intermetallic phases. The annealed LPBF microstructure, by comparison, combines a favorable solute partitioning with more coherent interfaces, which is deemed responsible for an increased sensitization resistance when benchmarked against the as-built and hot-rolled conditions. This demonstrates that LPBF components, when appropriately heat-treated, can offer advantages over conventionally processed DSS for use in demanding environments
Deep learning-enabled discovery of low-melting-point ionic liquids
No full textIonic liquids (ILs) are salts that are liquids at ambient conditions (typically below 373 K) and are known for their many unique properties, including low volatility and high thermal stability. Despite the promise of ILs, their targeted design is challenging for several reasons, including (i) the vast number of candidate ions that could be synthesised as components of an IL, (ii) the lack of predictive methods to determine what ion combinations will yield ILs with desired melting points, and (iii) experimentally known ILs possess limited chemical diversity. In this work, we present a data-driven framework for designing novel low-melting-point ILs. We model ILs as bipartite graphs and apply a link prediction algorithm to identify promising cation–anion pairs, expanding the collected IL database more than 30-fold, while prioritising low melting points. To further explore chemical space, we trained variational auto-encoders (VAEs) to generate new IL candidates through learning a latent space that enables modelling the data distribution. A thermodynamics-inspired classification model is subsequently employed to filter out ILs predicted to melt above 373 K. Finally, molecular dynamics simulations validate our approach, confirming that 18 out of 20 generated ILs have melting points below 373 K
Transplacental antibody transfer: mechanisms, pregnancy-related disruptions, and emerging experimental models
No full textThe transplacental transfer of maternal immunoglobulin G from the mother to the foetus is central for providing immunity in early life, resulting in full-term newborns having IgG repertoires and levels similar to those of their mothers. The neonatal Fc receptor is recognised as the primary transporter of IgGs across the placental epithelium. Understanding the mechanisms of transplacental antibody transfer and factors that affect them is essential in optimising maternal vaccination strategies, ultimately protecting infants from various environmental pathogens. This review first outlines the biological mechanisms governing transplacental IgG transfer, followed by a discussion of how this process may be disrupted by physiological and pathological conditions during pregnancy, including preterm birth, hypergammaglobulinemia, maternal pathogenic IgG, maternal infections, hyperglycaemia, and exposure to biological therapies. We also summarise currently available models used to study transplacental IgG transfer, highlighting existing knowledge gaps and future directions for research in this field