Publications

Chronic kidney disease (CKD) is a common non-communicable disease in children, and kidney dysfunction is the leading metabolic risk factor for death. Despite this, awareness of the CKD burden remains limited, and significant inequities exist in access to diagnosis and care worldwide. Kidney disease risk in children begins in utero and is dependent on the mother's health and wellbeing. This is further impacted each day by poverty, nutrition, education, infection, and safety. Greater community awareness is needed, especially in lower resource settings, where children present late and may have no access to care. Early diagnosis, possibly supported by screening at schools, can have important public and individual health consequences. Catastrophic health expenditure is common if families attempt to pay out of pocket for kidney replacement therapy. Health systems require strengthening from the antenatal clinic through tertiary care to ensure children with kidney disease are identified and treated early, appropriately, affordably, and well. Local non-governmental organizations have had some success in mitigating inequities. Governments must step up, measure, and acknowledge the burden of kidney disease in children, ensure appropriate public health measures to reduce risk, strengthen primary care to improve the quality of diagnosis and care, and progressively scale up equitable access to all forms of kidney care. Kidney disease risk is strongly linked with social and structural determinants of health. A holistic approach to supporting child wellbeing-outlined by the Sustainable Development Goals and a One Health Approach-will positively impact child kidney health and promote equity among all children.

BACKGROUND: The benefits of physical activity (PA) for both physical and mental health, including major depressive disorder (MDD), are well established. Mobile devices, such as smartphones, offer a scalable way to monitor PA and its relationship with depressive symptoms in daily life.

OBJECTIVE: This study aimed to investigate the association between passive smartphone-recorded step counts and current depressive symptoms in individuals with and without a lifetime diagnosis of MDD, using a naturalistic bring-your-own-device approach.

METHODS: We used the Remote Monitoring Application in Psychiatry (ReMAP) to collect passive step count data from participants' personal smartphones. The sample included 181 individuals with a lifetime MDD diagnosis, assessed via the structured clinical interview for the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition; DSM-IV), and 195 healthy controls (HCs). Current depressive symptoms were assessed using the Beck Depression Inventory. PA was operationalized as daily and weekly step counts, passively recorded via smartphone sensors. Hierarchical models were applied to examine the association between PA and depression severity.

RESULTS: Patients with MDD exhibited significantly lower daily step counts (mean 3454, SD 2683) compared to HCs (mean 4699, SD 3175; P<.001) and showed reduced diurnal variability (β=-0.36; P=.003). Higher daily step counts were associated with lower Beck Depression Inventory scores across the full sample (β=-0.06, 95% CI -0.09 to -0.02; P=.002), with similar trends in both MDD and HC groups. Weekly step counts also significantly predicted lower concurrent depressive symptoms (β=-0.29, 95% CI -0.43 to -0.14; P<.001), while patients with MDD displayed less variability in weekly activity levels than HCs (β=-0.75; P=.001).

CONCLUSIONS: These findings underscore the potential of mobile devices to be used as effective tools for monitoring PA in patients with MDD, supporting more customized and adaptive approaches to prevention and treatment. They also emphasize the importance of incorporating PA into the clinical management of depression.

INTRODUCTION: Intimate partner violence (IPV) has been associated with various adverse health outcomes, and these outcomes may be worse in those experiencing IPV-related head injuries. Cognitive, motor, and psychiatric symptoms associated with these exposures are incompletely understood.

METHODS: In this cross-sectional survey study, participants completed questionnaires assessing demographics, IPV-related exposure, depression, anxiety, cognitive, and neurobehavioral symptoms. Participants were stratified into groups 1) without IPV history ('controls,' n = 1032), 2) with IPV history without IPV-related head injury ('IPV-only,' n = 163), and 3) with IPV-related head injury ('IPV-HI,' n = 102). ANCOVAs and logistic regressions controlling for age, sex, and race were used for comparison with subsequent pairwise comparisons using Tukey's post-hoc and estimated marginal means.

RESULTS: IPV groups had greater rates of all psychiatric conditions reported, general health problems including sleep difficulties and chronic pain, and motor symptoms (all p < 0.05). Compared to IPV-only, the IPV-HI group reported greater rates of migraines, chronic pain, and suicidal ideation, as well as greater anxiety, cognitive difficulties, and neurobehavioral symptoms (all p < 0.05).

CONCLUSION: IPV groups reported more health issues than controls, and those with IPV-HI had the greatest rates of general health, cognitive, psychiatric, and neurobehavioral difficulties. These findings provide novel insight into IPV and IPV-related head injury outcomes.

AIMS: In the follow-up of patients with mitral regurgitation (MR), assessment of left ventricular (LV) dilatation using standard echocardiography often yields inconsistent results. We investigated whether measuring 3D LV end-systolic volume (3DLVESV) improves risk stratification in moderate or greater MR.

METHODS AND RESULTS: In the prospective 3D Echocardiography and Cardiovascular Prognosis in Mitral Regurgitation (3D-PRIME) study, 227 patients -142 with primary (PMR) and 85 secondary MR (SMR)- underwent 2D/3D echocardiography. 3DLVESV was increased if ≥41.5/35 mL/m², and LV end-systolic diameter (LVESD) enlarged if ≥39.8/34.8 mm in men/women. The primary outcome was a composite of MR progression towards intervention, death, or heart failure hospitalization (HFH). Death or HFH was a secondary outcome.At baseline, 28% of PMR and 54% of SMR patients had increased 3DLVESV. After 21 (15-25) months, increased 3DLVESV was associated with 1.9-fold (1.2-3.2) higher adjusted risk of the primary outcome in PMR, and 4.1-fold (1.6-10.7) higher risk of death or HFH in SMR (P < 0.05). 3DLVESV and LVESD concordantly identified LV dilatation in 20% of PMR patients and were discordant in 27%. Both patients with increased 3DLVESV only, and those with increased both 3DLVESV and LVESD, had high risk of the primary outcome after adjusting for recommendations for intervention in PMR: HR 7.1 (2.9-16.9) and 4.9 (2.1-11.1), respectively (P < 0.001).

CONCLUSION: Increased 3DLVESV is associated with a higher risk of adverse events in patients with significant MR. In PMR, evaluating LV dilatation using both 3DLVESV and LVESD may enhance risk stratification and aid in patient selection for close follow-up.

CLINICALTRIALSGOV IDENTIFIER: NCT04442828, 17 April 2020.

This Perspective explores the transformative potential of piezoelectric biomaterials in addressing one of the most persistent challenges in craniomaxillofacial (CMF) bone regeneration: the reliable healing of large, irregular, and functionally demanding skeletal defects. Traditional approaches─autologous grafts, allografts, and inert synthetic scaffolds─are limited by donor-site morbidity, immunogenicity, mechanical insufficiency, and inadequate bioactivity. In contrast, piezoelectric materials offer a dynamic alternative, generating endogenous-like electrical cues in response to mechanical stress, thereby mimicking the body's natural bone homeostasis and healing mechanisms. Bone's intrinsic piezoelectricity plays a critical role in cellular behavior through electromechanical signaling. Inspired by this, exogenous piezoelectric scaffolds─composed of polymers (e.g., PVDF, PLA), ceramics (e.g., BaTiO3, HA), or their composites─have been engineered to convert physiological strain into localized electric potentials that activate osteogenic pathways and modulate immune responses. In vitro and in vivo studies consistently demonstrate enhanced osteoblast proliferation, differentiation, mineralization, and macrophage polarization toward pro-healing phenotypes. Notably, BaTiO3/PLA membranes, magnetically or mechanically activated composites, and 3D-printed piezoelectric scaffolds have shown accelerated bone formation and vascularization in preclinical CMF defect models. Beyond bone repair, these materials exhibit antimicrobial and immunomodulatory properties, making them uniquely suited for complex, load-bearing, and inflamed environments such as mandible or periodontal defects. The convergence of advanced fabrication techniques (e.g., electrospinning, 3D/4D printing) and smart materials design now enables patient-specific, bioactive implants capable of real-time mechanotransduction. While no human trials have yet been reported, the clinical trajectory is supported by existing FDA-approved piezoelectric devices and growing preclinical validation. Future progress hinges on overcoming translational barriers, including regulatory clearance, scalable manufacturing, and mechanical reliability under functional loads. Ultimately, piezoelectric biomaterials represent a next-generation paradigm for CMF regeneration, combining mechanical support, immunomodulation, and bioelectric stimulation to enable personalized and robust bone regeneration.

BACKGROUND: Diagnosing cardiac amyloidosis (CA) on echocardiography can be challenging due to the imaging overlap between CA and more prevalent causes of a hypertrophic phenotype. This study sought to (1) evaluate the performance of artificial-intelligence (AI) derived measurements incorporated into the established multiparametric echocardiographic scoring system to detect CA; (2) develop and validate an AI-based deep-learning model for video-based detection of CA on echocardiography.

METHODS: The study population comprised 5776 patients (CA, 2756; controls, 3020). The training data set included patients from the UK National Amyloidosis Center and Taiwan MacKay Memorial Hospital (CA, 2241; controls, 2130). External test data sets were obtained from the US Duke University Health System (CA, 334; LVH controls, 668) and Japan National Cerebral and Cardiovascular Center (CA, 181; LVH controls, 222).

RESULTS: The multiparametric echocardiographic score computed using AI-derived measurements achieved an accuracy of 79.5% (sensitivity, 75.4%; specificity, 81.5%) in the United States cohort and 79.7% (sensitivity, 81.6%; specificity, 78.1%) in the Japan cohort. The deep-learning model demonstrated accuracies of 96.2% (sensitivity, 96.8%; specificity, 95.7%) and 95.8% (sensitivity, 97.3%; specificity, 94.3%) in the internal validation and internal test sets, respectively. External validation of the deep-learning model showed accuracies of 87.5% (sensitivity, 86.6%; specificity, 87.9%) in the United States and 88.4% (sensitivity, 92.3%; specificity, 85.3%) in the Japanese cohort. Subgroup analysis demonstrated that the deep-learning model showed robust discrimination of CA from other hypertrophic phenocopies: CA versus hypertension (area under the curve [AUC], 0.92 [95% CI, 0.91-0.94]), CA versus hypertrophic cardiomyopathy (AUC, 0.91 [95% CI, 0.87-0.94]), CA versus aortic stenosis (AUC, 0.93 [95% CI, 0.90-0.95]), CA versus chronic kidney disease (AUC, 0.93 [95% CI, 0.91-0.95]). The deep-learning model was able to classify a greater proportion of patients compared with the AI-derived multiparametric echocardiographic score and achieved superior diagnostic accuracy (AUC, 0.93 [95% CI, 0.91-0.95] versus AUC, 0.88 [95% CI, 0.85-0.90]; P<0.001).

CONCLUSIONS: Both the multiparametric echocardiographic score computed from AI-derived measurements and the fully automated deep-learning model can accurately identify patients with CA in globally diverse cohorts, with the deep-learning model providing superior performance.

BACKGROUND: Preparation for radioiodine (RAI) therapy in differentiated thyroid cancer (DTC) often requires thyroid hormone withdrawal (THW) to achieve thyrotropin (TSH) stimulation. Current guidelines recommend TSH ≥30 mIU/L, a target that prolongs hypothyroidism and worsens quality of life, yet rests on limited evidence.

OBJECTIVE: To evaluate the association between pre-RAI TSH levels and oncologic outcomes in adults with DTC prepared by THW.

METHODS: We conducted a systematic review and meta-analysis of studies comparing outcomes across pre-RAI TSH thresholds (<30 vs. ≥30, <60 vs. ≥60, and <90 vs. ≥90 mIU/L) in adults with DTC prepared by THW. Primary outcomes included disease-specific mortality, recurrence, and response to therapy. Searches in MEDLINE, Embase, Cochrane, and Scopus (inception to March 2025) identified eligible studies. Risk of bias was assessed using the CLARITY tool and certainty of evidence using GRADE. Pooled relative risks (RRs) were calculated using random-effects models. This systematic review was registered in PROSPERO (CRD42020158354).

RESULTS: This meta-analysis included eight retrospective cohort studies comprising a total of 4651 DTC patients, predominantly women (68.5%) with a mean age of 46 years. All patients underwent THW before RAI. Across all TSH thresholds examined (<30, <60, and <90 mIU/L), higher pre-RAI TSH levels were not associated with better treatment response, lower recurrence, or reduced mortality. Specifically, patients with higher pre-RAI TSH levels (≥30 mIU/L) did not have better oncologic outcomes compared with those with lower levels (<30 mIU/L). At 2- and 3-year follow-up, no significant differences were observed in excellent (pooled RR = 0.87; confidence interval [CI] 0.68-1.11) or indeterminate (RR = 1.28; CI 0.72-2.27) response rates. Similarly, recurrence rates did not differ (RR = 1.45; CI 0.83-2.55), and no study demonstrated a difference in disease-specific mortality across follow-up periods extending up to 10 years. The certainty of evidence for all outcomes was rated very low due to risk of bias, heterogeneity, and imprecision.

CONCLUSIONS: The current evidence base is insufficient to support or refute the routine use of a specific TSH threshold before RAI administration. These findings question the recommendation to achieve TSH ≥30 mIU/L before RAI and highlight the need for trials to define the minimal effective level of TSH stimulation.

INTRODUCTION: Cognition is a common symptom dimension in major mood disorders and is associated with impairments in daily life functioning. Assessments that capture cognitive difficulties reflective of those that people experience in the real world are therefore much needed; however, most cognitive assessments lack ecological validity. A recently developed, fully immersive VR platform for cognitive assessment (CAVIR) has proven to be feasible, well-tolerated, sensitive to cognitive impairment in psychiatric populations, and associated with measures of daily functioning. Here we aimed to assess the validity of a newly developed English language version of CAVIR in people with primary mood disorders (PMD) and controls (HC).

METHOD: We enrolled 40 people with PMD including Bipolar I Disorder, Bipolar II Disorder, and Major Depressive Disorder, and 40 healthy controls. Participants were administered the CAVIR, the MATRICS Consensus Cognitive Battery (MCCB), symptom ratings, and measures of daily functioning (FAST, UPSA-B).

RESULTS: Patients scored worse than controls on the CAVIR composite and all subtests (p = 0.02-p < 0.0001), except the executive functioning task (p = 0.85). Comparing the composite and domain scores of CAVIR to their corresponding domains on the MCCB revealed modest to moderate, significant correlations on the composite and all domains except executive functioning. The CAVIR was associated with both performance-based (UPSA-B) and interview rated (FAST) measures of functioning.

CONCLUSIONS: This newly translated English language version of CAVIR performed very similarly to the original version and was sensitive to cognitive impairments in people with PMD. CAVIR composite and most subtests were correlated with an established paper and pencil cognitive battery and were associated with measures of functioning. The CAVIR is self-administered, quick, and requires minimal training, making it a useful tool for assessing cognition.

Ancient DNA studies revealed that, in Europe from 6500 to 4000 BCE, descendants of western Anatolian farmers mixed with local hunter-gatherers resulting in 70-100% ancestry turnover1, then steppe ancestry spread with the Corded Ware complex 3000-2500 BCE2. Here we document an exception in the wetland, riverine and coastal areas of the Netherlands, Belgium and western Germany, using genome-wide data from 112 people 8500-1700 BCE. A distinctive population with high (approximately 50%) hunter-gatherer ancestry persisted 3,000 years later than in most European regions, reflecting incorporation of female individuals of Early European Farmer ancestry into local communities. In the western Netherlands, the arrival of the Corded Ware complex was also exceptional: lowland individuals from settlements adopting Corded Ware pottery had hardly any steppe ancestry, despite a Y-chromosome characteristic of people associated with the early Corded Ware complex. These distinctive patterns may reflect the specific ecology that they inhabited, which was not amenable to full adoption of the early Neolithic type of farming introduced with Linearbandkeramik3, and resulted in distinct communities where transfer of ideas was accompanied by little gene flow. This changed with the formation of Lower Rhine-Meuse Bell Beaker users by fusion of local people (13-18%) and Corded Ware associated migrants of both sexes. Their subsequent expansion then had a disruptive impact across a much wider part of northwestern Europe, especially in Great Britain where they were the main source of a 90-100% replacement of local Neolithic ancestry.