The research team, led by Yuying Li and Panpan Li of Nanjing University of Finance and Economics together with Kaichao Shao of Yellow River Conservancy Technical University, drew on the China Family Panel Studies, one of the country’s most comprehensive longitudinal social surveys. The CFPS covers 25 provinces, municipalities and autonomous regions representing about 95 percent of China’s population. Because the marital satisfaction question was only fielded in certain waves, the analysts used data from 2014, 2018, 2020 and 2022, restricting the sample to married adults aged 20 to 60 and excluding anyone who divorced or remarried during the study window. After trimming extreme values, the final dataset comprised 10,716 individuals interviewed at least twice, yielding 29,734 observations. The average respondent was about 44 years old, had been married for roughly 23 years, and carried a mean BMI of 23.67, with 43.49 percent classified as overweight or obese under Chinese standards.

Technically, the study treated BMI as a continuous outcome and estimated ordinary least squares regressions with marriage duration and its squared term as the key explanatory variables, alongside controls for age, education, self-rated health, smoking, drinking, family size, household income, the Engel coefficient of food spending and the number of children. Provincial, year and age-group fixed effects absorbed regional economic conditions, survey-period shocks and the nonlinear influence of age on metabolism. Across the full sample, the linear coefficient of marriage duration was 0.0638 and the quadratic coefficient was −0.0013, both significant at the 1 percent level. For men the linear term rose to 0.0764, about 8.68 percent higher than the female estimate of 0.0703. A formal U-test confirmed the inverted U-shape and located the turning points at approximately 24.5 years for the full sample, 23.9 years for men and 25.1 years for women.

To make sense of this curve, the authors integrated two classic frameworks. Grossman’s health capital model views health as a form of capital that people deliberately invest in, subject to intertemporal trade-offs. McCubbin and Patterson’s Double ABC-X model describes how families buffer external stressors by mobilizing resources and reconfiguring cognition. In early marriage, the combined pressures of family building and career development raise the opportunity cost of health investment. Slow weight gain has not yet produced perceptible harm, so its health depreciation is underestimated and the expected marginal benefit of healthy behavior stays low. Resources flow toward market labor and childcare, squeezing out healthy food consumption and physical exercise. Health capital decelerates or even depreciates, and body weight climbs. Later in marriage, as excess weight begins to generate medical costs, psychological strain and relational friction, the discounted value of averting future health losses finally exceeds the cost of lifestyle adjustment. Families then reallocate resources toward joint health plans, coordinated diets and regular exercise, and reframe weight management as the maintenance of shared family assets. The authors are careful to note that the framework served as a heuristic guide, since direct measures of stressors, coping resources and cognitive appraisals were not available in the data.

The gender gap has a sociological logic. Gender role theory holds that society assigns men and women different family expectations. Men often occupy the breadwinner role, with their value tied to income and status rather than body shape, so after marriage they may pay less attention to weight management. Women face countervailing forces: marriage provides economic support and emotional value, and women frequently act as family health gatekeepers who reinforce healthy habits, yet the dual burden of paid work and unpaid domestic labor creates time scarcity and chronic stress that crowd out exercise and nutrition, while sociocultural norms pressure women to stay thin and penalize them more harshly for weight gain in employment and marriage. Prior Chinese and American studies have consistently found marriage associated with overweight risk only or more strongly in men, and the new findings fit that pattern.

The robustness checks are unusually thorough. Replacing BMI with body weight in kilograms and with a binary overweight indicator produced the same inverted U-shape, with the linear coefficient for body weight 42.49 percent larger for men than for women and the coefficient for overweight risk 16.67 percent larger. Excluding municipalities and autonomous regions, and separately excluding the 2020 and 2022 waves affected by the COVID-19 pandemic, left the conclusions intact, with the gender gap widening to 25.20 percent when pandemic-period samples were dropped. A province–year fixed effects specification controlled for time-varying regional confounders, and an instrumental variables approach used the relative age at first marriage, defined as the deviation between an individual’s actual age at first marriage and the provincial 2010 census average, to address endogeneity. The instrument was strong by Kleibergen-Paap diagnostics, and the IV estimates remained qualitatively consistent with the baseline, though the authors treat them as supplementary rather than definitive causal identification.

Heterogeneity analyses revealed where the marriage effect bites hardest. Among parents, the inverted U-shaped relationship was robust for the full sample and for both sexes, whereas among the small non-parent subsample of 498 observations it emerged only for men, with childless men showing a steeper early-marriage BMI increase consistent with the honeymoon effect. The association was 56.60 percent larger in rural than in urban areas, plausibly reflecting narrower premarital dietary diversity and greater potential for post-marital dietary shifts during China’s ongoing nutrition transition. Regionally, the linear coefficient was 29.20 percent larger in northern China, where a wheat-based dietary pattern combines high carbohydrate intake with low animal protein, than in the south, whose rice-based pattern features more vegetables, fish and poultry. Northern men and women both showed stronger marriage–BMI associations than their southern counterparts.

The most striking result concerns marital satisfaction. Measured on a five-point Likert scale, satisfaction was mean-centered and interacted with marriage duration and its square. For men, the interaction between satisfaction and the linear term was negative and significant, indicating that higher marital satisfaction weakens the positive association between marriage duration and BMI. For women, none of the interaction terms were significant. A reverse-causality check regressing current satisfaction on lagged BMI among men found no significant coefficient, supporting the interpretation that satisfaction buffers weight gain rather than the other way around. The authors speculate that satisfied couples may shift their lifestyle synchrony from shared eating toward joint health-promoting behaviors such as exercising together and monitoring each other’s diets, echoing a four-year longitudinal study of 169 newlywed couples that linked spousal supportive behavior to slower weight gain.

Limitations temper the celebration. BMI alone cannot capture visceral or abdominal adiposity, which is more strongly tied to metabolic risk, and self-reported height and weight introduce measurement error. The quadratic specification ignores repeated fluctuations between normal, overweight and obese states, and marital quality is captured only by subjective satisfaction, omitting conflict, support and dyadic coping. Panel attrition from requiring at least two interviews may bias estimates. The authors call for group-based trajectory models, Markov state transition analyses and multi-wave studies to clarify causal dynamics.

Even so, the implications are considerable. Obesity is projected to rise at an annual rate of 5.4 percent in China from 2020 to 2035, reaching an adult obesity rate of 18 percent, with the economic burden of overweight estimated at 1.27 trillion dollars, or 3.1 percent of GDP. Worldwide, one in eight people was living with obesity in 2022. By showing that the marriage–weight relationship is nonlinear, gender-specific, household-specific and region-specific, and that relationship quality matters for men’s weight trajectories, the study lays an empirical foundation for obesity prevention strategies built around the family as a unit, sensitive to gender and region. The magic of love, it turns out, is not that marriage makes people heavy, but that a good marriage may eventually help men lighten up.

Subject of Research: Health

Article Title: The magic of love: gender differences in marriage duration and body mass index

Article References: Li, Y., Li, P., & Shao, K. (2026). The magic of love: gender differences in marriage duration and body mass index. Frontiers in Nutrition, 13, Article 1867171. https://doi.org/10.3389/fnut.2026.1867171

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1867171

Keywords: obesity, marriage, BMI, China Family Panel Studies, marital satisfaction, gender differences, public health, Frontiers in Nutrition, magic, love, gender, differences

The single most powerful lever, the analysis confirms, is weight loss. Every additional percentage point of total body weight lost raised the odds of remission by 5 percent (odds ratio 1.05, 95 percent confidence interval 1.04 to 1.07). When the researchers examined categorical thresholds, the effect became dramatic: patients who lost at least 10 percent of their body weight were nearly three times as likely to achieve remission as those who did not (OR 2.98). In one included study, patients shedding 20 percent or more of their weight within a year of surgery had more than four times the remission odds of those losing less. Crucially, this weight-loss effect held in both surgical and non-surgical groups, with the non-surgical subgroup showing a remarkably tight estimate (OR 1.07, with essentially no heterogeneity). The message is that the mechanism matters less than the kilograms.

That conclusion dovetails with the well-known DiRECT trial, in which a primary-care-led very low-calorie diet allowed 46 percent of patients with early type 2 diabetes to reach remission at one year — and among those who lost 15 kilograms or more, the remission rate soared to 86 percent. The biological explanation most often invoked is the twin cycle hypothesis proposed by Roy Taylor: excess fat accumulating in the liver and pancreas impairs insulin sensitivity and beta-cell function, and draining that ectopic fat restores both. The new meta-analysis adds population-scale statistical weight to that mechanistic story, suggesting that any intervention capable of producing sustained weight loss — whether a scalpel or a diet plan — moves patients toward remission.

But the study’s headline surprise lies in body mass index itself. Baseline BMI behaved in opposite directions depending on the intervention. Among patients undergoing bariatric or metabolic surgery, each additional unit of BMI increased the odds of remission (OR 1.05 per kg/m²), while among non-surgical patients, higher BMI reduced those odds (OR 0.89 per kg/m²). The between-group difference was highly significant. The authors are careful to flag caveats: the non-surgical estimate rested on only two studies, and confounding by indication — heavier patients being steered toward surgery, lighter ones toward lifestyle programs — may partly manufacture the divergence. Still, the plausible interpretation is that a higher starting weight gives surgery more metabolic ground to reclaim, whereas without the intervention, a higher BMI simply reflects a harder-to-shift metabolic state.

Timing emerged as the other dominant theme. Each additional year of diabetes duration lowered remission odds by 11 percent (OR 0.89 per year), and patients diagnosed less than five years earlier were more than three times as likely to remit as those with longer-standing disease (OR 3.41). Age told a parallel story: each additional year reduced remission odds by 4 percent, and patients aged 45 or younger had 2.39 times the remission odds of older patients. The physiological logic is straightforward. Early in the disease, beta cells have endured less chronic exposure to elevated glucose and lipids — the processes of glucotoxicity and lipotoxicity — so their insulin-secreting capacity is more recoverable once metabolic pressure is lifted. The window for reversal, in other words, is real and measurable.

Glycemic markers at baseline painted the same picture from a different angle. Higher fasting plasma glucose and higher HbA1c each independently reduced remission odds (OR 0.99 per mg/dL and 0.91 per percentage point, respectively). When studies were pooled by categorical thresholds, patients starting below 7 percent HbA1c had nearly triple the remission odds of those above it (OR 2.98), and those below 8 percent had more than double the odds (OR 2.25). Treatment intensity carried similar signal: each additional oral antidiabetic agent cut remission odds by nearly half (OR 0.56), and insulin use was associated with a 66 percent reduction (OR 0.34). The authors interpret heavy medication burdens not as causes of failed remission but as markers of more severe, long-standing beta-cell dysfunction — a clinical shorthand for how much metabolic ground has already been lost.

Lifestyle factors produced a more mixed verdict. Smoking was consistently associated with lower remission odds (OR 0.90), a finding with low heterogeneity across studies and a plausible mechanism, since chronic tobacco exposure drives oxidative stress and inflammation that erode insulin sensitivity. In the non-surgical subgroup, continued alcohol consumption reduced remission odds while alcohol cessation raised them (OR 1.14). Yet physical exercise and intermittent fasting showed no significant independent association with remission — a result the authors attribute cautiously to small study numbers, but which also hints that a single behavioral lever may not matter unless it actually produces weight loss. Equally striking were the null results for gender, race and ethnicity, HOMA-IR, and pooled C-peptide levels, though individual studies of C-peptide, a proxy for beta-cell reserve, did report strong positive associations with remission that quantitative pooling could not confirm due to inconsistent assay methods.

The team’s methodology was deliberately conservative. Remission was defined uniformly as HbA1c below 6.5 percent measured at least three months after stopping all glucose-lowering drugs, and studies were stratified by whether they used this strict definition or looser criteria. Subgroup analyses revealed that the choice of remission definition was itself a major source of the heterogeneity that has plagued earlier reviews — for gender, for instance, the pooled estimate flipped direction between strict and non-strict definitions. Sensitivity analyses using leave-one-out elimination and comparisons of fixed- and random-effects models confirmed that the key associations — age, duration, HbA1c, BMI, medication count, insulin use, and weight loss — were robust. Publication bias was detected only for baseline HbA1c, and a trim-and-fill adjustment that added four hypothetical missing studies still left the association statistically significant.

The clinical implications are concrete. The analysis identifies actionable thresholds: lose at least 10 percent of body weight, act within five years of diagnosis, and aim for HbA1c below 7 percent before expecting remission to be realistic. It also suggests a division of labor between treatment modalities — surgery may offer the better route for patients with higher BMI, while intensive lifestyle modification and pharmacotherapy may serve those with lower BMI or those unsuitable for operations. The authors are candid about limitations: most included studies were retrospective, some subgroups contained too few studies for formal interaction testing, and the findings apply only to established type 2 diabetes, not prediabetes, where recent evidence suggests remission may confer distinct cardiovascular protection. Even so, for a condition affecting hundreds of millions worldwide, the study reframes the prognosis. Remission is not a lottery; it is a race against beta-cell decline, and the evidence now says the earlier and the more weight lost, the better the odds of crossing the finish line without a daily pill regimen.

Subject of Research: Factors influencing remission of type 2 diabetes across surgical and non-surgical interventions

Article Title: Influencing factors of type 2 diabetes remission: a systematic review and meta-analysis

Article References: Cheng, S., Chen, J., Zhang, X., Qi, H., Kang, X., Nie, W., Feng, Y., & Chen, R. (2026). Influencing factors of type 2 diabetes remission: a systematic review and meta-analysis. Frontiers in Endocrinology, 17, Article 1916734. https://doi.org/10.3389/fendo.2026.1916734

Image Credits: AI Generated

DOI: 10.3389/fendo.2026.1916734

Keywords: type 2 diabetes, remission, meta-analysis, bariatric surgery, weight loss, HbA1c, beta-cell function, BMI, lifestyle intervention, insulin use, DiRECT trial, systematic review

The research team enrolled 128 participants, dividing them into four groups: 30 normal-weight healthy controls with BMI between 18.5 and 23.9 kg/m², 31 overweight or obese individuals without diabetes whose BMI was 24.0 kg/m² or higher, 33 normal-weight patients with newly diagnosed T2DM, and 34 overweight or obese patients with T2DM. All participants underwent comprehensive echocardiographic assessment, including conventional ultrasound measurements and advanced 2D-STI analysis of right ventricular free wall strain, early diastolic strain rate (SRe), and late diastolic strain rate (SRa).

Right ventricular function was evaluated through multiple complementary parameters. The researchers measured right ventricular free wall global longitudinal strain (RVFWS), tricuspid annular plane systolic excursion (TAPSE), right ventricular fractional area change (FAC), and the SRe/SRa ratio, which reflects the balance between early and late diastolic relaxation of the right ventricle. They also assessed the myocardial performance index (MPI) and right ventricular outflow tract Doppler velocities to capture a complete picture of right-sided cardiac performance.

The results revealed a clear stepwise pattern of right ventricular deterioration across the four groups. Normal-weight healthy controls showed the best right ventricular performance, while overweight or obese individuals without diabetes already displayed measurable impairment in RVFWS and diastolic strain rates compared with their lean counterparts. Patients with normal-weight T2DM showed further declines, and those who carried both excess weight and diabetes exhibited the most severe right ventricular dysfunction of all four groups, with the lowest RVFWS values and the most abnormal SRe/SRa ratios.

Statistical analysis confirmed that both BMI and T2DM status independently contributed to right ventricular impairment, and that the combination produced a more pronounced effect than either factor alone. Two-way analysis of variance demonstrated significant main effects of BMI and diabetes on RVFWS, SRe, SRa, and the SRe/SRa ratio, along with a significant interaction between the two factors for several parameters. This interaction suggests that obesity and diabetes do not merely add their separate harms to the right ventricle but may amplify each other’s damaging influence through overlapping metabolic and inflammatory pathways.

Multiple linear regression analysis strengthened the case for BMI as a key driver of right ventricular damage. After adjusting for age, sex, heart rate, blood pressure, and glycemic control, BMI remained an independent predictor of reduced RVFWS and abnormal diastolic strain rates in the combined patient population. The findings indicate that every additional unit of BMI carries a measurable cost for right ventricular mechanics, even in people whose diabetes is newly diagnosed and not yet complicated by advanced cardiovascular disease.

The study also explored whether conventional echocardiographic parameters could detect the same pattern of right ventricular dysfunction. While TAPSE and FAC showed some differences between groups, these traditional measures were less sensitive than 2D-STI strain parameters in distinguishing early subclinical changes. This observation underscores the value of speckle tracking technology, which tracks the movement of individual speckles within the myocardial tissue frame by frame, providing a more nuanced assessment of regional cardiac deformation than visual estimation or single-plane measurements.

Mechanistically, the researchers propose several pathways through which excess adiposity and hyperglycemia converge to injure the right ventricle. Increased visceral fat promotes chronic systemic inflammation, elevates circulating free fatty acids, and fosters insulin resistance, all of which can impair cardiomyocyte metabolism and promote myocardial fibrosis. At the same time, chronic hyperglycemia accelerates the formation of advanced glycation end products, increases oxidative stress, and disrupts calcium handling within cardiac cells. The right ventricle, with its thinner walls and greater dependence on subendocardial blood supply, may be particularly vulnerable to these combined metabolic insults.

The clinical implications of the study are significant for the millions of people worldwide living with both obesity and diabetes. Right ventricular dysfunction is increasingly recognized as a predictor of adverse outcomes in heart failure, pulmonary hypertension, and other cardiovascular conditions, yet it often goes undetected until the disease is advanced. The findings suggest that 2D-STI could serve as a practical screening tool to identify patients at risk of early right ventricular damage, allowing clinicians to intervene earlier with weight management, glycemic control, and other cardioprotective strategies before irreversible structural changes take hold.

The authors acknowledge several limitations of their work, including its cross-sectional design, which cannot establish causality or track how right ventricular function evolves over time. The study also focused on newly diagnosed patients without established cardiovascular complications, so the findings may not generalize to those with long-standing diabetes or advanced heart disease. Nevertheless, the research adds compelling evidence that the right ventricle deserves closer attention in metabolic disease, and that the combination of elevated BMI and T2DM represents a particularly potent threat to this underappreciated cardiac chamber. Future longitudinal studies using serial speckle tracking assessments could clarify how quickly right ventricular function declines with ongoing metabolic exposure and whether early interventions can preserve or restore normal cardiac mechanics.

Subject of Research: Right ventricular function in type 2 diabetes and obesity

Article Title: Assessment of the impact of body mass index on right ventricular systolic and diastolic function in patients with type 2 diabetes mellitus using two-dimensional speckle tracking imaging

Article References: Wang, W., Peng, Y., Zhao, K., Zheng, Z., Feng, J., Zou, C., Sun, Y., Lin, B., Wang, L., Hu, B., & Yang, S. (2026). Assessment of the impact of body mass index on right ventricular systolic and diastolic function in patients with type 2 diabetes mellitus using two-dimensional speckle tracking imaging. Frontiers in Clinical Diabetes and Healthcare, 7, Article 1694955. https://doi.org/10.3389/fcdhc.2026.1694955

Image Credits: AI Generated

DOI: 10.3389/fcdhc.2026.1694955

Keywords: type 2 diabetes, obesity, right ventricle, speckle tracking, echocardiography, cardiac strain, diastolic function, BMI, cardiometabolic risk, subclinical dysfunction, Assessment, impact

The research, published in Frontiers in Urology by a team led by Manuela Montatore and Giuseppe Guglielmi across the Universities of Foggia and hospitals in Brindisi, Bisceglie, and Barletti, examined 40 men who started ADT at Antonio Perrino Hospital in Brindisi between January 2023 and May 2025. Every patient had a contrast-enhanced CT scan within 30 days before treatment began and a technically comparable follow-up scan roughly a year later. Instead of ordering new imaging, the team extracted quantitative body-composition data from these existing oncologic examinations, an approach known as opportunistic imaging. The results paint a striking picture of simultaneous deterioration across three tissue compartments that conventional clinical measures largely missed.

The technical logic of the study rests on a well-validated principle of quantitative radiology: a single axial CT section at the third lumbar vertebra (L3) serves as a reliable surrogate for whole-body tissue composition. Using semiautomated threshold-based segmentation with attenuation windows of −29 to +150 Hounsfield units for muscle, −190 to −30 HU for subcutaneous fat, and −150 to −50 HU for visceral fat, the researchers measured the skeletal muscle index (SMI), bilateral psoas muscle attenuation, the subcutaneous adipose tissue index (SATI), and the visceral adipose tissue index (VATI). They then extended the analysis into the skeleton itself, placing oval regions of interest within the trabecular bone of the L1 to L3 vertebral bodies to capture vertebral attenuation, an opportunistic marker of bone health that no prior longitudinal ADT study has combined with muscle and fat in the same imaging framework.

After approximately twelve months of androgen suppression, the changes were substantial and consistent. Mean skeletal muscle index fell from 48.4 to 45.5 cm²/m², a relative decline of 6.0 percent. Mean psoas attenuation, which reflects the radiodensity of muscle tissue and indirectly captures fatty infiltration, dropped from 41.0 to 37.8 HU, a 7.8 percent reduction. Subcutaneous fat increased by 11.6 percent and visceral fat by 6.2 percent, while mean vertebral trabecular attenuation declined by 4.4 percent, from 132.1 to 126.3 HU, suggesting concurrent loss of bone quality. Twenty-three of the forty patients, or 57.5 percent, lost at least 5 percent of their skeletal muscle index, a prespecified exploratory threshold. All of these changes reached statistical significance, with p-values ranging from 0.018 to below 0.001.

What makes these findings especially compelling is what did not change: body mass index. BMI rose only modestly, from 26.7 to 27.0 kg/m², a difference that was not statistically significant, and the correlation between BMI change and SMI change was weak and nonsignificant (Spearman ρ = 0.24). The most telling statistic concerns the 23 men with clinically meaningful muscle loss: fifteen of them, or 65.2 percent, had a stable or increased BMI over the same period. Fat gain had effectively masked muscle depletion on the scale. This adiposity-driven camouflage means that a clinician relying on weight or BMI alone could wrongly conclude that a patient is tolerating treatment well, even as his metabolic reserve and physical resilience erode beneath a stable surface.

The study also explored whether any baseline feature could predict who would suffer the steepest muscle decline. In a deliberately parsimonious three-variable logistic regression model restricted to age, baseline psoas attenuation, and metastatic status, lower baseline psoas attenuation emerged as the only factor associated with a 5 percent or greater SMI decline, with an odds ratio of 1.14 per 1-HU decrease. Patients who ultimately lost the most muscle had started with noticeably darker, more fat-infiltrated muscle on their initial scans, averaging 38.9 HU compared with 43.8 HU in those with smaller declines. The authors are careful to frame this as hypothesis-generating: with only 40 patients, the model cannot establish psoas attenuation as an independent predictive biomarker, but it raises the possibility that a single number extracted from a pre-treatment scan could one day flag men at highest risk before therapy begins.

Why should androgen deprivation remodel muscle, fat, and bone simultaneously? Testosterone is an anabolic hormone that supports protein synthesis in skeletal muscle and suppresses adipogenesis. When it is pharmacologically eliminated, muscle catabolism accelerates, fat accumulates preferentially in visceral depots, and the delicate coupling between muscle and skeleton weakens. These compartments are not independent silos; they communicate through mechanical loading, hormonal signaling, inflammatory pathways, and metabolic crosstalk. A growing body of evidence links these tissue changes to hard clinical outcomes. Previous work has associated skeletal muscle loss during ADT with increased non-cancer mortality in high-risk prostate cancer, and more recent longitudinal studies have connected ADT-induced muscle loss and fat gain to subsequent cardiovascular events, suggesting that body composition may be a barometer of whole-patient vulnerability beyond oncologic status alone.

The reproducibility data strengthen the case that these measurements are robust rather than artifacts of measurement technique. When a second blinded radiologist independently re-analyzed ten patients’ paired scans, interobserver agreement was excellent: intraclass correlation coefficients reached 0.97 for SMI, 0.94 for psoas attenuation, 0.98 for SATI, 0.97 for VATI, and 0.93 for vertebral trabecular attenuation. The team also enforced strict technical comparability, requiring all paired scans to use the same portal venous contrast phase, matched tube voltage (120 kVp in 87.5 percent of pairs), and similar reconstruction thickness, because enhancement phase and acquisition parameters can shift attenuation values and contaminate longitudinal comparisons. Vertebral analysis proved feasible in 92.5 percent of potentially assessable vertebral levels, with metastatic involvement, compression deformities, or artifacts accounting for the few exclusions.

Important caveats temper the enthusiasm. The study was retrospective, single-center, and small, and it lacked an untreated comparator group, so the observed remodeling cannot be attributed exclusively to ADT. Aging, cancer progression, chemotherapy, radiotherapy, androgen-receptor pathway inhibitors, comorbidities such as diabetes and cardiovascular disease, and lifestyle factors may all have contributed. The five deaths recorded during follow-up were far too few for any survival inference, and the vertebral attenuation values from contrast-enhanced scans were explicitly not treated as DXA-equivalent bone mineral density or as diagnostic of osteoporosis. Patients who died before the follow-up scan could not contribute to the paired analysis, introducing potential survival bias. The authors emphasize that the study demonstrates feasibility, not proven clinical benefit, and that no treatment decisions should yet be triggered by these measurements.

Even so, the implications are provocative. CT scans are among the most common examinations in oncology, acquired routinely for staging, surveillance, and treatment assessment, and every one of them contains quantitative information about muscle, fat, and bone that currently goes unused. If larger, prospective, controlled studies confirm that integrated CT-derived phenotyping predicts fractures, metabolic complications, cardiovascular risk, or survival during ADT, then the humble staging scan could evolve into a longitudinal body-composition monitoring tool requiring no additional radiation, cost, or patient burden. For the millions of men worldwide who depend on androgen suppression to keep their cancer in check, the study suggests a future in which the price of treatment is measured not just in tumor control, but in the health of every tissue it touches, visible in images doctors already possess.

Subject of Research: CT-derived body composition changes during androgen deprivation therapy for prostate cancer

Article Title: Longitudinal CT-derived muscle–fat–bone remodeling following androgen deprivation therapy initiation in prostate cancer

Article References: Montatore, M., Muscatella, G., Masino, F., Muscogiuri, E., & Guglielmi, G. (2026). Longitudinal CT-derived muscle–fat–bone remodeling following androgen deprivation therapy initiation in prostate cancer. Frontiers in Urology, 6, Article 1985221. https://doi.org/10.3389/fruro.2026.1985221

Image Credits: AI Generated

DOI: 10.3389/fruro.2026.1985221

Keywords: androgen deprivation therapy, prostate cancer, computed tomography, body composition, skeletal muscle index, sarcopenia, visceral adiposity, vertebral trabecular attenuation, opportunistic imaging, bone health, BMI, oncology

The study was conducted by Gülsevim Oda of the Department of Pediatric Dentistry at Ankara Yildirim Beyazit University and Emine Merve Ekici of the Department of Nutrition and Dietetics at the University of Health Sciences in Ankara. Their work set out to answer a deceptively simple question: do family-level lifestyle practices, dietary quality, and body weight leave a visible signature in a child’s mouth? To find out, the researchers recruited children aged six to thirteen years and combined clinical dental examinations with validated questionnaires assessing diet and household habits, along with anthropometric measurements of body composition.

Adherence to the Mediterranean dietary pattern was measured using the Mediterranean Diet Quality Index for Children and Adolescents, widely known by its abbreviation KIDMED. This instrument evaluates consumption of foods considered protective, such as fruit, vegetables, fish, and olive oil, alongside items considered detrimental, including sweets, sugary drinks, and regularly skipping breakfast. The family environment was assessed with the Family Nutrition and Physical Activity Screening Tool, or FNPA, which captures household practices such as meal patterns, food availability, screen time limits, and opportunities for physical activity. Together, these tools allowed the investigators to look beyond the individual child and examine the family context in which eating and activity behaviors are formed.

The clinical side of the study was equally rigorous. Each child underwent a dental examination in which researchers recorded caries experience using the standard indices: dmft and dmfs for primary teeth, and DMFT and DMFS for permanent teeth, counting decayed, missing, and filled teeth or surfaces. Periodontal status was evaluated with the gingival index and the plaque index, which quantify gum inflammation and bacterial biofilm accumulation, respectively. Body weight status was expressed as a BMI-for-age z-score, a measure that accounts for a child’s age and sex when comparing body mass index against population reference data. All statistical analyses were performed using SPSS software, version 27.0.

The descriptive results painted a familiar but sobering picture of contemporary pediatric lifestyles. Just over half of the participants, 52.5 percent, showed moderate adherence to the Mediterranean diet, while 29.4 percent of the children were classified as obese. That nearly one in three children in the sample carried excess weight underscores the double burden facing pediatric health systems, where overnutrition and poor dietary quality coexist with preventable dental disease. The researchers note that the study was registered as a clinical trial, NCT06130189, on November 13, 2023, and received ethics approval from the Ankara Medipol University Local Ethics Committee, with written informed consent obtained from parents and assent from the children themselves.

When the researchers examined the correlations between their measures, a coherent pattern emerged. KIDMED scores, reflecting Mediterranean diet adherence, were positively correlated with FNPA scores, indicating that children whose families practiced healthier nutrition and activity habits also tended to eat better themselves. More strikingly, higher KIDMED scores were negatively correlated with both the gingival index and the plaque index, meaning that children eating a more Mediterranean-style diet had less gum inflammation and less plaque on their teeth. FNPA scores, in turn, showed negative correlations with dmft and dmfs, suggesting that supportive family environments were associated with less caries experience in the primary dentition.

Body weight told the opposite story. The BMI-for-age z-score was positively correlated with DMFT, DMFS, gingival index, and plaque index, indicating that children with higher body mass index carried more caries burden in their permanent teeth and showed worse periodontal indicators. This convergence of metabolic and oral health markers in childhood is significant because it mirrors associations documented in adult populations, where obesity and periodontal disease frequently travel together, possibly through shared inflammatory pathways, dietary patterns high in processed foods and sugars, and behavioral factors that influence both conditions simultaneously.

The most important results came from the multivariable analyses, in which the researchers adjusted for age, sex, BMI-for-age z-score, family nutrition and physical activity practices, and toothbrushing frequency. Even after accounting for these potential confounders, higher Mediterranean diet adherence remained independently associated with lower DMFT scores and lower gingival index values. In other words, the apparent protective effect of the Mediterranean diet on permanent-tooth caries and gum health was not simply explained by children brushing more often, weighing less, or coming from healthier households. Conversely, higher BMI-for-age z-scores remained independently associated with poorer periodontal health, reinforcing the link between excess weight and gum inflammation in children.

The biological plausibility behind these associations is worth unpacking. The Mediterranean diet is rich in antioxidants, fiber, vitamins, and anti-inflammatory compounds from olive oil, fresh produce, legumes, and fish, all of which may support immune function and reduce the inflammatory burden that drives gingival disease. Whole foods requiring chewing also stimulate saliva production, which buffers acids and helps remineralize enamel, while the diet’s characteristic low intake of free sugars deprives cariogenic bacteria of their preferred substrate. By contrast, diets dominated by ultra-processed foods provide a steady supply of fermentable carbohydrates that fuel acid production by oral bacteria, eroding enamel and promoting the dysbiosis associated with both caries and periodontal inflammation.

The authors are careful to emphasize the limits of their design. Because the study is cross-sectional, capturing a single moment in time, no causal inferences can be drawn; it remains possible that children with painful or diseased mouths alter their diets, or that unmeasured factors such as socioeconomic status, access to dental care, or fluoride exposure shape both diet and oral health. The researchers call for longitudinal and interventional studies to confirm whether improving dietary quality actually protects children’s teeth and gums. Even so, the findings carry a practical message for families, pediatricians, and dentists alike: oral health may be another beneficiary of the Mediterranean eating pattern, and the dinner table, alongside the bathroom sink, may be one of the most powerful tools for keeping children’s smiles healthy. The research received no specific grant funding, and the authors declare no competing interests.

Subject of Research: Associations between Mediterranean diet adherence, family nutrition and physical activity practices, BMI, and oral health in children

Article Title: The relationship of mediterranean diet adherence, family nutrition and physical activity practices, and BMI with oral health in children

Article References: Oda, G., & Ekici, E. M. (2026). The relationship of mediterranean diet adherence, family nutrition and physical activity practices, and BMI with oral health in children. BMC Pediatrics. https://doi.org/10.1186/s12887-026-07477-z

Image Credits: AI Generated

DOI: 10.1186/s12887-026-07477-z

Keywords: Mediterranean diet, children, oral health, dental caries, BMI, obesity, periodontal health, KIDMED, family nutrition, physical activity, pediatric dentistry, cross-sectional study

The research team, led by Wang Pukui of Fuzhou University together with colleagues from the Capital University of Physical Education and Sports, Capital Normal University, and Guangzhou Sport University, recruited 1,346 first- to third-year undergraduate students between May 14 and June 3, 2025, using convenience cluster sampling. Participants completed two validated instruments: the Academic Sub-Scale, which measures perceived academic stress, and the Chinese-translated Behavioral Regulation in Exercise Questionnaire-2, which captures the full spectrum of exercise motivation as described by self-determination theory. Rather than treating stress and motivation as single continuous variables, the researchers used Mplus 8.3 to search for hidden subgroups of students who share similar combined patterns across all of these dimensions simultaneously.

Latent profile analysis is a person-centered statistical method that has gained traction in psychology precisely because it acknowledges a fundamental truth about human behavior: populations are rarely homogeneous. Instead of averaging everyone together and reporting a single correlation coefficient, the technique identifies unobservable categories, or latent profiles, that best explain the patterns of responses in the data. Model fit was evaluated using standard information criteria and classification diagnostics, and the researchers settled on a four-profile solution as the optimal balance between statistical parsimony and explanatory power. To probe which demographic characteristics predicted membership in each profile, they employed the R3STEP method, a three-step approach that allows researchers to relate predictors to latent class assignment while accounting for classification uncertainty.

The four profiles that emerged paint a strikingly varied picture of student life. The smallest group, comprising 9.0 percent of the sample, was labeled the High stress-low motivation profile. These students reported elevated academic stress alongside low scores on every dimension of exercise motivation, a combination that the authors suggest may represent a particularly vulnerable state in which the demands of coursework crowd out any drive for physical activity. At the opposite end of the motivational spectrum, 7.4 percent of students fell into the High stress-high motivation profile, exhibiting both the highest academic stress and the highest levels of external, introjected, and identified regulation, the more controlled and partially internalized forms of motivation on the self-determination continuum.

The third group, accounting for 22.1 percent of participants, was termed the Low stress-high autonomy profile. These students reported the lowest academic stress and the highest intrinsic motivation, meaning they exercised for the sheer enjoyment and satisfaction the activity itself provides rather than for external rewards or internal pressure. The final and by far the largest group, the Moderate-balanced adaptation profile, encompassed 61.6 percent of the sample. These students scored moderately on all measured variables, suggesting a kind of functional equilibrium in which academic demands and exercise motivation coexist without either dominating. The sheer size of this middle group is itself informative: most students, according to this data, are neither thriving nor collapsing but muddling through in a moderate zone.

What makes these findings particularly compelling is the demographic patterning that underlies the profiles. Students with normal weight showed a significantly stronger probability of belonging to three of the four profiles, the High stress-high motivation group, the Low stress-high autonomy group, and the Moderate-balanced adaptation group, compared with their overweight and obese counterparts. This pattern hints at a possible bidirectional relationship between body composition and the psychological architecture of motivation, though the cross-sectional design of the study prevents any firm conclusions about causation. It may be that students who maintain healthy weight are more likely to possess the self-regulatory resources that support both academic coping and sustained exercise, or that the reverse is true, or that both are shaped by common underlying factors.

Gender and academic seniority also mattered. Female students and third-year students demonstrated a lower probability of belonging to the High stress-low motivation profile, the group that researchers would most want to identify early for targeted support. This suggests that women and more advanced students in this sample may possess protective characteristics, whether psychological, social, or experiential, that buffer them against the doubly adverse combination of high stress and low motivation. Meanwhile, geographic and socioeconomic background left its own fingerprint: rural students exhibited a stronger probability of association with the Low stress-high autonomy profile, whereas urban students were more likely to belong to the Moderate-balanced adaptation profile. The authors interpret these differences through the lens of self-determination theory and the strength model of self-control, frameworks that posit that autonomous motivation and self-regulatory capacity are finite resources that can be depleted by sustained demands.

The theoretical implications extend beyond the campus. The study provides empirical support for applying self-determination theory, one of the most influential frameworks in contemporary motivational psychology, to the specific context of academic stress. According to this theory, motivation exists on a continuum from fully external regulation, in which behavior is driven by rewards and punishments, through introjected and identified regulation, in which the person gradually internalizes the value of the behavior, to intrinsic motivation, in which the behavior is its own reward. The finding that a distinct subgroup of highly stressed students displays elevated controlled motivation, while a low-stress subgroup displays high intrinsic motivation, is consistent with the idea that stress may shift individuals toward more controlled forms of behavioral regulation, potentially at a cost to long-term sustainability.

For university administrators and health professionals, the practical message is that one-size-fits-all wellness programs may be leaving the most vulnerable students behind. The 9.0 percent of students in the High stress-low motivation profile represent a clearly identifiable target group for differentiated interventions, while the 7.4 percent in the High stress-high motivation profile may need help converting their pressured, externally driven exercise habits into more autonomous and sustainable forms. The authors argue that their findings offer targeted references for implementing differentiated mental health and physical exercise interventions in higher education settings, an approach that could involve screening students for stress-motivation profiles and tailoring support accordingly.

The researchers are careful to note the limitations of their work. Convenience cluster sampling, while efficient, means the sample may not be representative of all Chinese college students, and the authors explicitly caution against extrapolating their conclusions to the entire population. The study was supported by the Philosophy and Social Science Planning Project of Fujian Province and was approved by the Ethics Committee of the Capital University of Physical Education and Sports, with all participants providing informed consent in accordance with the Declaration of Helsinki. Even with these caveats, the study offers a fresh and statistically rigorous way of thinking about the intertwined fates of academic pressure and physical activity, revealing that behind the averages lie four very different student realities, each demanding its own response.

Subject of Research: Latent profiles of academic stress and exercise motivation among Chinese college students

Article Title: Latent profiles of academic stress and exercise motivation among college students: A latent profile analysis

Article References: Pukui, W., Zihao, L., Xiangyu, W., & Xiang, G. (2026). Latent profiles of academic stress and exercise motivation among college students: A latent profile analysis. BMC Psychology. https://doi.org/10.1186/s40359-026-05509-y

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05509-y

Keywords: college students, academic stress, exercise motivation, latent profile analysis, self-determination theory, physical exercise, mental health, BMI, intrinsic motivation, higher education, psychology, China

The research team, led by Alia Iftikhar of King Edward Medical University in Lahore, Pakistan, set out to answer two related questions. First, does vitamin D supplementation actually raise serum levels of 25-hydroxyvitamin D, the standard laboratory measure of vitamin D status, in children whose body fat stores tend to sequester the nutrient? Second, if levels do rise, does that translate into measurable improvements in body mass index, blood lipids, insulin sensitivity, or markers of cardiovascular risk? To find out, the researchers searched PubMed, Embase, and Google Scholar using a structured search string that combined terms for vitamin D, obesity and overweight, randomized trials, and pediatric populations.

The screening process identified 24 studies that met the inclusion criteria, spanning trials of varying formulations, dosages, and durations. Of these, 11 randomized controlled trials provided data suitable for quantitative meta-analysis. The team assessed the methodological quality of the included studies using the Cochrane Risk of Bias tool, known as ROB-2, which evaluates potential sources of bias in randomized trial design, conduct, and reporting. Follow-up periods across the trials ranged from as short as eight weeks to as long as twelve months, with assessments conducted at intervals including three, six, and twelve months.

The primary outcome, serum vitamin D levels, showed a clear and statistically significant benefit from supplementation. In the meta-analysis, children assigned to vitamin D supplementation had serum 25-hydroxyvitamin D concentrations that exceeded those of placebo recipients by a standardized mean difference of 3.12 nanograms per milliliter, with a 95 percent confidence interval of 1.72 to 4.52. In practical terms, this means that supplementing children with overweight or obesity does correct the relative deficiency that their larger fat stores tend to create, even if the magnitude of the increase varies from trial to trial.

Why would children with obesity be prone to low vitamin D in the first place? The answer lies in the chemistry of the molecule itself. Vitamin D, specifically 25-hydroxycholecalciferol, is lipophilic, meaning it dissolves readily in fat rather than water. In people with larger adipose depots, a greater fraction of circulating vitamin D partitions into fat tissue, effectively diluting the amount available in the bloodstream. Researchers have described this as volumetric dilution rather than simple sequestration, and studies dating back more than a decade have documented the inverse relationship between body fat indexes and vitamin D status in adolescents. The new analysis confirms that supplementation can overcome this dilution effect, at least partially.

The safety picture was reassuring. Across the included trials, no adverse events were reported following supplementation, an important finding given that some of the studies tested relatively high doses of the vitamin. Vitamin D toxicity, which can cause hypercalcemia and kidney problems, is a legitimate concern at very high intakes, but the pooled evidence suggests that the regimens used in these pediatric trials were well tolerated. For clinicians weighing whether to treat documented deficiency in young patients with obesity, the analysis offers support for the safety of doing so.

The secondary outcomes tell a more sobering story. The review observed some favorable signals, including decreases in body mass index, serum triglycerides, and inflammatory markers among supplemented children. However, when the researchers examined the broader picture of metabolism and cardiovascular health, the effects did not reach statistical significance. Insulin sensitivity, a key determinant of future type 2 diabetes risk, did not improve consistently, and cardiovascular risk markers overall remained essentially unchanged. In other words, raising blood vitamin D levels did not translate into the cardiometabolic benefits that observational studies had hinted at.

This disconnect between vitamin D status and metabolic outcomes is consistent with a growing body of evidence across age groups. Observational studies have repeatedly linked low vitamin D levels with obesity, insulin resistance, and cardiovascular disease, but such associations are notoriously vulnerable to confounding, since obesity itself drives both low vitamin D and poor metabolic health. Randomized trials, which isolate the effect of supplementation, have generally been less enthusiastic. Previous systematic reviews of vitamin D supplementation in children and adolescents have similarly found little consistent effect on cardiometabolic outcomes, and trials in obese adolescents have reported that even large doses sometimes fail to alter cardiovascular risk factors or beta-cell function.

The authors of the new analysis are careful about what their findings do and do not support. Vitamin D supplementation in children with overweight or obesity corrects deficiency and significantly raises serum levels without adverse events, they conclude, but new trials should be conducted to identify effective therapies that genuinely enhance metabolic and cardiovascular outcomes in this population. That framing matters, because it redirects attention away from vitamin D as a standalone intervention and toward the harder question of what actually improves insulin sensitivity, lipid profiles, and vascular health in young people with excess weight.

For families and clinicians, the practical takeaways are relatively straightforward. Children and adolescents with obesity are at elevated risk of vitamin D deficiency, which can compromise bone mineralization during a critical window of skeletal development, and supplementation is a safe and effective way to restore adequate blood levels. But parents hoping that a daily capsule will melt away metabolic risk are likely to be disappointed. The evidence now suggests that vitamin D is a necessary nutrient whose correction supports bone health, while the deeper drivers of cardiometabolic disease in pediatric obesity, including diet quality, physical activity, and sustained weight management, require interventions of a different kind. The 24 studies synthesized in this review, drawn from populations as diverse as South Asian, African American, Hispanic, Sri Lankan, and European children, collectively close one chapter on vitamin D in pediatric obesity and open another: the search for therapies that move the needle on the outcomes that matter most.

Subject of Research: Effects of vitamin D supplementation on serum vitamin D levels and cardiometabolic health outcomes in children and adolescents with overweight or obesity

Article Title: Effect of vitamin D supplementation on serum vitamin D levels and health outcomes in pediatric population with obesity/overweight: a systematic review and meta-analysis

Article References: Iftikhar, A., Iftikhar, M. R., Iftikhar, M. R., & Malik, A. (2026). Effect of vitamin D supplementation on serum vitamin D levels and health outcomes in pediatric population with obesity/overweight: a systematic review and meta-analysis. International Journal of Obesity. https://doi.org/10.1038/s41366-026-02231-y

Image Credits: AI Generated

DOI: 10.1038/s41366-026-02231-y

Keywords: vitamin D, pediatric obesity, meta-analysis, systematic review, cholecalciferol, insulin sensitivity, cardiovascular risk, BMI, 25-hydroxyvitamin D, children, adolescents, supplementation

The research, conducted by Bowen Yang and Long Jin of the hospital’s Department of Interventional Radiology, took a deliberately multifaceted approach to the problem. Rather than relying on a single dosimetric number, the team analyzed three complementary radiation metrics in 100 patients who underwent PTCD. The first was fluoroscopy time, the total duration of live X-ray imaging during the procedure. The second was cumulative dose, which reflects the intensity of the radiation beam integrated over the exposure time. The third was dose-area product, which combines the cumulative dose with the size of the irradiated field, capturing how much tissue is exposed as well as how strongly. Each metric tells a different part of the story, and the researchers argued that only by examining all three together can clinicians understand where radiation risk truly originates.

The statistical strategy behind the study is worth appreciating, because it addresses a subtle trap in radiation research. Fluoroscopy time, cumulative dose, and dose-area product are not independent quantities. Cumulative dose is, by definition, dose rate multiplied by exposure time, and dose-area product is cumulative dose multiplied by the irradiated field area. If a researcher simply throws all three into a regression model alongside patient characteristics, the results become difficult to interpret, since the dose metrics are physically entangled with one another. Yang and Jin solved this by building a chain of multivariate generalized linear models using a Gamma distribution with a log link, a choice well suited to skewed, strictly positive dosimetric data. Fluoroscopy time was retained as a covariate in the cumulative dose model, and both fluoroscopy time and cumulative dose were retained in the dose-area product model. This allowed the team to partition the intrinsic physical contribution of exposure duration and dose intensity, so that any remaining significant factors could be interpreted as influences on each dose component beyond those mechanical relationships.

The findings on fluoroscopy time were among the most striking. Three factors emerged as significant predictors. Patients in whom the drainage was accessed via a subxiphoid route, rather than a dual approach, had substantially shorter fluoroscopy times, with the model estimating the subxiphoid route at roughly a third of the dual route’s exposure duration. Obstruction located at the hepatic hilum, as opposed to the common bile duct, was also associated with shorter fluoroscopy time, a somewhat counterintuitive result that may reflect differences in how easily guidewires and catheters can be maneuvered depending on where the blockage sits. Finally, older age predicted shorter fluoroscopy times, with each additional year of age corresponding to a small but statistically significant reduction. Taken together, these results suggest that the geometry of the access path and the location of the obstruction shape how long operators must work under continuous imaging.

When the researchers turned to cumulative dose after adjusting for fluoroscopy time, a different set of drivers came into focus. The dominant predictor was body mass index. Heavier patients absorbed markedly more radiation, with each unit increase in BMI associated with a roughly nine percent increase in cumulative dose. This makes physical sense: more tissue between the X-ray source and the detector forces the machine to increase output to penetrate the body, raising the dose delivered for every second of imaging. Female sex was associated with lower cumulative dose, and interestingly, patients with less severe intrahepatic ductal dilatation also received lower doses than those with severe dilatation, an association that reached statistical significance. Longer fluoroscopy time, unsurprisingly, remained a strong predictor of higher cumulative dose, confirming that duration and dose intensity both matter independently.

The dose-area product model, which adjusts for both fluoroscopy time and cumulative dose, told a converging story. Higher BMI again emerged as a significant predictor, as did longer fluoroscopy time and higher cumulative dose, each contributing independently to the total energy imparted across the irradiated field. Older age also predicted higher dose-area product, standing in contrast to its association with shorter fluoroscopy time. This divergence is instructive: in older patients, procedures may be quicker, but the dose delivered per unit time or per unit area can still be greater, perhaps reflecting anatomical changes or technical adjustments in beam settings. The lesson is that no single metric can stand in for the full radiation picture, and a procedure that looks efficient on one measure may still carry substantial dosimetric burden on another.

What do these findings mean in practice? The authors conclude that patient BMI is associated with overall radiation exposure, making body habitus a key variable to consider when planning and counseling patients before PTCD. Procedural complexity, reflected in the level of biliary obstruction, the choice of access route, and the severity of ductal dilatation, shows significant associations with fluoroscopy time and cumulative dose. In concrete terms, an interventional team facing an obese patient with severe ductal dilatation and a dual access plan can anticipate a higher radiation burden and take countermeasures: minimizing fluoroscopic runs, using last-image hold and other dose-saving features, collimating tightly to reduce the irradiated field area, and rotating staff positions to limit scatter exposure. Because scatter radiation to operators scales with the dose leaving the patient, every reduction in patient dose also translates into occupational protection.

The study’s design carries both strengths and limitations that readers should keep in view. Its use of three linked dosimetric metrics and a statistically careful modeling chain represents a methodological advance over single-outcome analyses, and the retrospective cohort of 100 patients from a single high-volume center provides internally consistent evidence. However, the authors themselves are explicit that these findings are exploratory and warrant validation in larger, prospective studies. A retrospective single-center design cannot capture every variable that influences radiation use, including operator experience, equipment generation, and institutional protocols, all of which may vary widely across hospitals. The effect sizes for some predictors, while statistically significant, are modest, and clinical decision-making should not rest on any single coefficient.

Even so, the study arrives at a moment when radiation safety in interventional radiology is under growing scrutiny. Procedures like PTCD are becoming more common as populations age and biliary disease burden rises, and cumulative occupational exposure among interventionalists is a persistent concern for the specialty. By identifying which patients and which procedural configurations predict the highest doses, the Beijing team has given clinicians a framework for pre-procedural radiation awareness, one that treats dosimetry not as an afterthought recorded at the end of a case but as a dimension of planning on par with access strategy and catheter selection. If larger prospective studies confirm these associations, the humble BMI measurement and the anatomical mapping performed before a needle ever touches the skin could become standard inputs into a personalized radiation risk estimate, turning routine clinical data into a shield for both patients and the physicians who treat them.

Subject of Research: Predictors of patient radiation exposure during percutaneous transhepatic cholangiodrainage

Article Title: Predictors of radiation exposure in percutaneous transhepatic cholangiodrainage: a multifactorial analysis integrating fluoroscopy time, cumulative dose, and dose-area product

Article References: Yang, B., & Jin, L. (2026). Predictors of radiation exposure in percutaneous transhepatic cholangiodrainage: a multifactorial analysis integrating fluoroscopy time, cumulative dose, and dose-area product. BMC Medical Imaging. https://doi.org/10.1186/s12880-026-02817-y

Image Credits: AI Generated

DOI: 10.1186/s12880-026-02817-y

Keywords: PTCD, radiation protection, fluoroscopy time, cumulative dose, dose-area product, interventional radiology, BMI, biliary drainage, radiation dosimetry, generalized linear models, Predictors, radiation

The research team, led by Xichao Zhang of Harbin Sport University and corresponding author Hongwei Qiao, analyzed data from 1,258 children aged three to six years collected in 2020 through monitoring programs and caregiver questionnaires. Caregivers reported whether their child met recommended sleep duration, and 344 of the children, or 27.3 percent, were classified as having insufficient sleep. That figure alone is striking: more than one in four preschoolers in this cold-region population falls short of sleep recommendations, a prevalence consistent with growing global concern about young children’s sleep health.

What makes the study methodologically interesting is the discipline of its pipeline. The authors first excluded any variable with more than 15 percent missing data, then split participants into training and internal validation sets in a 7:3 ratio, stratified by outcome so that both sets contained similar proportions of short and adequate sleepers. Missing values were handled with multivariate imputation by chained equations, a technique that fills gaps by modeling each incomplete variable as a function of the others. Crucially, the imputation model was fitted only in the training set and then applied unchanged to the validation set, preventing information from leaking between the two groups, a common and subtle error in machine learning studies.

Feature selection followed a similar logic of restraint. Standardization and least absolute shrinkage and selection operator, or LASSO, regression were used to whittle the candidate variables down to a compact set, with all tuning confined to training data. LASSO retained six predictors: body mass index, weekend moderate-to-vigorous physical activity, weekend outdoor physical activity, weekend screen time, standing long jump performance, and two-leg consecutive jumping time. The prominence of weekend variables is notable, hinting that the structure of family life on non-school days, when routines loosen and outdoor opportunities shift, may be where insufficient sleep leaves its clearest traces.

With features selected, the team trained and compared seven classifiers, evaluating them on discrimination, classification metrics, calibration, and decision curve analysis. Light Gradient Boosting Machine posted the highest area under the receiver operating characteristic curve at 0.849, with a 95 percent confidence interval of 0.806 to 0.889. But the random forest model emerged as the study’s workhorse because of its balanced overall profile: an AUC of 0.827, compared with 0.752 for conventional logistic regression, along with accuracy of 0.798, sensitivity of 0.553, specificity of 0.891, an F1 score of 0.600, and a Brier score of 0.143. The pattern is familiar to anyone who has compared flexible models with classical ones: the random forest traded some sensitivity for strong specificity, meaning it rarely mislabels a well-rested child as sleep-deprived, though it misses roughly half of the true short sleepers.

The interpretability layer is where the study aims to earn its keep. Using Shapley additive explanations, or SHAP, a technique borrowed from cooperative game theory that allocates credit for each prediction to individual features, the researchers ranked weekend outdoor activity, weekend moderate-to-vigorous physical activity, and body mass index as the most influential predictors. SHAP plots also revealed nonlinear relationships between features and model output, meaning the association between, say, physical activity and sleep insufficiency was not a simple straight line but shifted in strength and direction across the observed range. Such patterns are precisely the kind of hypothesis-generating material that linear models tend to smooth over, and they align with the idea that movement behaviors and sleep are intertwined components of a single 24-hour activity cycle.

The cold-region setting is more than geographic color. Heilongjiang’s long, severe winters can sharply curtail outdoor play, altering the seasonal rhythm of physical activity and light exposure that helps anchor children’s circadian systems. The authors are careful, however, not to overclaim a distinct cold-region sleep phenotype. Their stated aim was to test whether routinely collected behavior, body-size, and fitness indicators jointly characterize caregiver-reported insufficient sleep, and their conclusion is that such data do support an interpretable, nonlinear, multivariable framework, one that integrates dimensions of child health that are usually analyzed in isolation.

Equally important is what the authors say the model cannot do. They explicitly position the framework as a tool for multidimensional data integration, status characterization, and hypothesis generation for future prospective studies, not as a replacement for direct sleep assessment. The outcome itself was caregiver-reported, which introduces the possibility of reporting bias, and the cross-sectional design means the models capture associations rather than causes. Low sensitivity further underscores that no screening tool built on indirect indicators should be treated as a diagnostic instrument. External validation across regions, climates, and seasons, the authors write, is required before any broader application.

Still, the study lands at a moment of intense interest in explainable artificial intelligence for child health. Black-box predictors have long faced justified skepticism in medicine, and SHAP-based approaches offer a middle path: models flexible enough to capture nonlinear interactions, yet transparent enough for clinicians and public health practitioners to inspect which factors drive predictions. If weekend outdoor activity and vigorous play emerge repeatedly as the dominant signals, that points toward practical, modifiable targets, such as protecting time and space for active outdoor play on weekends, that could be tested in interventions aimed at improving preschool sleep.

The broader takeaway is a methodological one. Sleep in early childhood is embedded in a web of movement behaviors, body composition, and physical fitness, and the tools used to study it should reflect that entanglement. By showing that ordinary monitoring data, processed through a carefully validated and interpretable pipeline, can characterize insufficient sleep with respectable discrimination, the Heilongjiang team has sketched a template other regions could adapt, and a reminder that sometimes the clues to a child’s sleepless nights are already sitting in the school records, waiting for the right questions to be asked.

Subject of Research: Explainable machine learning prediction of insufficient sleep duration among preschool children in cold-region China

Article Title: Explainable machine learning for identifying insufficient sleep duration among preschool children in cold-region China: a cross-sectional study

Article References: Zhang, X., Diao, Y., Liu, Y., Jin, Z., Gao, W., Wang, L., & Qiao, H. (2026). Explainable machine learning for identifying insufficient sleep duration among preschool children in cold-region China: a cross-sectional study. BMC Public Health. https://doi.org/10.1186/s12889-026-29586-1

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29586-1

Keywords: insufficient sleep, preschool children, machine learning, random forest, SHAP, LASSO, physical activity, BMI, screen time, cold region, BMC Public Health, cross-sectional study

The study, published in BMC Endocrine Disorders, followed 108 Chinese men with prolactinoma who received dopamine agonist monotherapy and were tracked for more than a year at the single tertiary center. The mean age at diagnosis was 41.8 years, with a wide spread of roughly 15 years on either side. The disease burden at baseline was striking: the median starting prolactin concentration was 1,039 nanograms per milliliter, orders of magnitude above the normal range, and the median tumor volume was about 2,710 cubic millimeters. Nearly 77 percent of the men had macroadenomas, tumors large enough to be clearly visible and potentially compress surrounding structures, while only about 23 percent had smaller microadenomas. This skew toward advanced disease reflects a well-recognized pattern in male prolactinoma, where symptoms such as reduced libido, erectile dysfunction, and headaches are often dismissed or attributed to other causes until the tumor has grown substantially.

Over a mean follow-up of 2.84 years, the treatment worked remarkably well by most conventional standards. Prolactin levels normalized in 69.4 percent of patients, tumor volume shrank by at least half in 79.6 percent, and 54.6 percent achieved both prolactin normalization and recovery of testosterone, the key hormone of the male gonadal axis. In ten patients the tumor disappeared entirely on imaging — an outcome that was far more common in men with microadenomas, where complete disappearance occurred in 28 percent of cases, compared with just 3.6 percent of macroadenomas. That difference, statistically significant at P equals 0.001, underscores how much the starting tumor size shapes what patients can ultimately expect from medication alone.

But the headline numbers conceal the study’s central insight. When the researchers integrated prolactin control and tumor shrinkage into a single combined classification, they found that discordant responses were common. At the last follow-up, 56.5 percent of the men met the criteria for a good response — normal prolactin plus at least 50 percent tumor-volume reduction — while 36.1 percent fell into a partial response category, meaning one measure improved while the other lagged. Some men normalized their prolactin yet retained bulky residual tumors; others saw dramatic shrinkage while the hormone remained stubbornly elevated. Only 7.4 percent had a poor response, with neither prolactin control nor meaningful tumor reduction. In other words, more than a third of patients would have been misclassified by a single-endpoint assessment.

To move beyond static snapshots, the team built what they call a dynamic integrated response framework, evaluating patients at baseline, at three months, and at one year, and asking which measurements at each stage best predicted the final outcome. The statistical machinery behind this included group comparisons, stage-specific logistic regression, receiver-operating-characteristic analysis to identify cutoff values, and bootstrap internal validation to test the robustness of the models. Sensitivity analyses were used to confirm that the findings were not driven by particular subgroups or analytic choices. The result is a time-stamped map of treatment response rather than a single verdict rendered at the end of follow-up.

The predictors that emerged differed sharply by stage. At baseline, the only significant independent predictor of a final good response was body mass index: lower BMI was associated with better outcomes, with an odds ratio of 0.810 per unit increase in BMI. Why body weight should matter remains an open question, but the association hints at metabolic influences on dopamine agonist sensitivity or on tumor biology itself. By three months, the picture shifted to treatment dynamics: each 10 percent greater reduction in prolactin at that early checkpoint nearly tripled the odds of a final good response, with an odds ratio of 3.093. This suggests that the first three months of therapy are a critical window in which the tumor’s behavior reveals its long-term trajectory.

At the one-year mark, two factors independently predicted a good final response. Prolactin normalization by then carried an odds ratio of 17.712 — a very strong signal — while each additional 10 percent of tumor-volume reduction added a more modest but still significant benefit, with an odds ratio of 1.106. The receiver-operating-characteristic analysis translated these associations into practical exploratory thresholds: a prolactin reduction of at least 94.8 percent at three months, and an absolute prolactin level at or below 23.30 nanograms per milliliter at one year, best separated patients destined for good responses from the rest. These cutoffs are exploratory and require external validation, but they offer clinicians concrete numbers to watch at defined moments in follow-up.

The clinical implications are potentially far-reaching. Current guidelines for managing prolactinoma largely assess treatment success through individual endpoints, and a patient whose prolactin has normalized might be considered a treatment success even if a large tumor mass persists and continues to threaten vision or pituitary function. Conversely, a patient with marked tumor shrinkage but persistently elevated prolactin might be labeled a failure despite clear radiological benefit. The integrated framework distinguishes transitional partial responses — patients still moving toward full control — from persistent ones, allowing clinicians to intensify monitoring, adjust drug doses, or consider surgery or radiotherapy at the right time rather than too late. The authors emphasize that the framework is a candidate endpoint structure for future validation studies, not a finished clinical tool.

Several caveats temper the enthusiasm. The study was retrospective and drawn from a single center, which limits generalizability and leaves open the possibility of selection effects; patients who required surgery or radiotherapy during follow-up were excluded, which may have removed the most treatment-resistant cases from the analysis. The cohort was exclusively male and exclusively Chinese, and prolactinoma behavior and drug tolerance can vary across populations. The response classification, while logically constructed, is new and has not yet been tested prospectively or in independent cohorts. Still, the size of the cohort — 108 men followed for nearly three years on average — is unusual for a disease that is rare in men, and the internal validation strengthens confidence in the identified predictors.

For patients, the takeaway is cautiously optimistic. Dopamine agonist monotherapy achieved high rates of both biochemical and structural control across all tumor sizes in this cohort, confirming that pills alone can do the heavy lifting for most men with prolactinoma, even those presenting with large tumors and prolactin levels a thousand times above normal. For clinicians, the study argues for a more nuanced follow-up rhythm: check prolactin and MRI early, watch the trajectory rather than the snapshot, and recognize that a discordant response is not a contradiction but a distinct clinical state deserving its own management strategy. As endocrinology moves toward personalized, time-dependent assessment of chronic endocrine diseases, this integrated response framework offers a template that could extend well beyond prolactinoma — provided that future prospective studies confirm what this Shanghai cohort has revealed.

Subject of Research: Dopamine agonist monotherapy outcomes in men with prolactinoma

Article Title: Dynamic integrated response to dopamine agonist monotherapy in Chinese men with prolactinoma: a retrospective cohort study

Article References: Zheng, H., Hu, B., Xie, Y., Qu, X., Zhang, S., Ye, H., Li, Y., Lu, R., & Ji, L. (2026). Dynamic integrated response to dopamine agonist monotherapy in Chinese men with prolactinoma: a retrospective cohort study. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02636-w

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02636-w

Keywords: prolactinoma, dopamine agonist, prolactin, testosterone, pituitary adenoma, tumor volume, endocrinology, retrospective cohort, treatment response, BMI, macroadenoma, hormonal therapy