The analysis used data from ORESTES, a multicenter, longitudinal, retrospective observational study registered as NCT06321731. Eligible patients were aged 40 years or older, had a confirmed COPD diagnosis, initiated budesonide/glycopyrronium/formoterol fumarate dihydrate before June 2023 and had at least 12 months of clinical data before initiation. The observation period covered the 12 months before treatment and up to 12 months afterward, ending earlier if a patient discontinued therapy, was lost to follow-up or died. Patients were identified retrospectively from electronic medical records, and treatment decisions were made by physicians during routine care rather than according to a research protocol. At 12 months, 89.3% of the cohort were persistent with triple therapy; 6.6% had discontinued treatment, 3.8% had died and 0.4% were lost to follow-up.

The cohort had a mean age of 70.17 years, a mean time since COPD diagnosis of 7.32 years, and several indicators of substantial disease burden. A total of 66.4% of patients had experienced at least one exacerbation during the preceding year, 72.3% were classified as having a high-risk GesEPOC phenotype, 78.4% had modified Medical Research Council dyspnea scores of at least 2, and 50.9% were classified as GOLD E. Before triple therapy, annualized rates were 0.53 hospitalizations, 4.47 hospitalized days, 0.71 emergency room admissions, 1.89 primary care visits and 1.28 specialist visits per patient. Emergency visits were treated as a separate category and did not include episodes resulting in hospitalization. Rescue-medication use was based on prescriptions documented as actually used by patients rather than prescriptions merely issued.

After budesonide/glycopyrronium/formoterol initiation, annualized hospitalization rates declined to 0.47 per patient and hospitalized days to 4.06, corresponding to reductions of 12.9% and 9.2%. Emergency room admissions decreased to 0.62, a 12.0% reduction, while primary care visits fell to 1.80, or 4.9%. Specialist visits moved in the opposite direction, increasing 17.5% to 1.51 per patient. The investigators said this rise might partly reflect the hospital-based study design and continued follow-up in specialist respiratory clinics, but the observational records could not establish whether closer follow-up caused any of the changes in acute care. The annualized rate of actual short-acting beta-2 agonist use fell from 1.19 to 0.89 prescriptions per patient, a decrease of 25.5%.

Researchers translated these utilization measures into economic estimates from the perspective of the Spanish National Health System. Published Spanish unit costs were updated to 2026 values using the general Consumer Price Index from Spain’s National Statistics Institute. The functional unit for the estimates was one patient over 12 months, and unit costs were applied to cohort-level annualized measures of resource use. Before triple-therapy initiation, estimated healthcare resource costs averaged €2,599.46 per patient per year. Hospitalizations accounted for 88.5% of that amount, or €2,300.13, while emergency room admissions accounted for €101.57, primary care visits for €53.57 and specialist visits for €144.19. Following initiation, the overall estimate decreased by €200.11 to €2,399.35 per patient. Hospitalization costs produced a €210.59 reduction, emergency room costs a €12.14 reduction and primary care costs a €2.61 reduction, while specialist visit costs increased by €25.22.

The environmental model expressed resource use in kilograms of carbon-dioxide equivalent, combining published emission factors for hospitalizations, emergency room admissions, primary and specialist visits, patient transport and actual short-acting beta-2 agonist use. Transport-related emissions were estimated separately with Spanish travel-distance data and transport assumptions because the proxy distances used in the multinational framework were not considered sufficiently representative. Before initiation, total emissions associated with the selected care components were estimated at 245.43 kg CO2e per patient per year. Hospitalizations contributed 79.0%, or 193.96 kg CO2e, and actual rescue-medication use contributed 11.1%, or 27.27 kg CO2e. Emergency room admissions accounted for 5.2%, primary care visits 1.4% and specialist visits 3.2%. After initiation, the total fell by 25.16 kg CO2e to 220.27 kg CO2e.

Hospitalization-related emissions declined by 17.88 kg CO2e after treatment initiation, rescue-medication emissions by 6.94 kg CO2e, emergency room emissions by 1.53 kg CO2e and primary care emissions by 0.17 kg CO2e. Specialist-visit emissions increased by 1.37 kg CO2e. The emissions estimate was then tested under alternative assumptions about generic healthcare-contact factors, transport choices, vehicle electrification and travel distances. The modeled annual reduction ranged from 21.66 to 33.70 kg CO2e per patient across these scenarios, compared with the base-case estimate of 25.16 kg CO2e. Tested scenarios included varying generic healthcare-contact factors by plus or minus 25%, assuming all hospital and emergency travel used ambulances and other travel used private cars, increasing the electric-vehicle share from less than 1% to 20%, and applying the shortest and longest average travel distances reported across Spanish provinces. These sensitivity analyses supported the direction of the modeled result, although they did not remove the limitations of the observational comparison.

For system-level context, the authors multiplied the per-patient estimates by an external proprietary market estimate of 65,000 patients initiating triple therapy in Spain during 2025. This illustrative scenario implied approximately €13.0 million in annual healthcare-resource cost savings and 1,635 tons of avoided CO2e. The authors explicitly cautioned that the projection should not be interpreted as an observed national saving or emissions reduction. The economic and environmental analyses excluded maintenance inhaled therapies because complete longitudinal data for the pre-initiation period were unavailable and the previous inhaler devices could not be reliably inferred from recorded ingredients. Short-acting bronchodilator acquisition costs were omitted because their expected contribution was considered minimal. The selected resource and medication components also did not constitute a full environmental sustainability assessment of the COPD care pathway.

The results need to be interpreted within the design and scope of ORESTES. Its retrospective before-and-after comparison cannot establish that budesonide/glycopyrronium/formoterol caused the changes; regression to the mean and confounding by indication remain possible, and no paired longitudinal model, covariate adjustment, formal hypothesis testing or missing-data imputation was used. Data came from hospital-based records, potentially limiting generalizability to primary-care-led COPD services, and the analysis did not separately compare patients escalating from dual therapy with those switching from another triple regimen. It also was not a cost-effectiveness study: it included no concurrent comparator, health-utility outcome or incremental cost-effectiveness ratio. The multicenter cohort, use of routine electronic records and integration of economic and environmental estimates nevertheless provide descriptive real-world evidence that improvements in acute healthcare use after treatment optimization can coincide with lower modeled costs and emissions.

Subject of Research: Estimated healthcare costs, resource use and greenhouse gas emissions after COPD triple-therapy initiation in Spain

Article Title: Impact of Budesonide/Glycopyrronium/Formoterol Initiation on Healthcare Resource Utilization and Estimated Associated Costs and Greenhouse Gas Emissions Across COPD Care in Spain (ORESTES* Study)

Article References: Figueira-Gonçalves, J. M., Alcázar-Navarrete, B., Ancochea, A., Lastres, T., de Andrés-Nogales, F., Corregidor-García, C., Fitas, E., & Sánchez-Covisa, J. (2026). Impact of Budesonide/Glycopyrronium/Formoterol Initiation on Healthcare Resource Utilization and Estimated Associated Costs and Greenhouse Gas Emissions Across COPD Care in Spain (ORESTES* Study). Advances in Therapy. https://doi.org/10.1007/s12325-026-03817-8

Image Credits: AI Generated

DOI: 10.1007/s12325-026-03817-8

Keywords: COPD, triple therapy, budesonide, glycopyrronium, formoterol, healthcare utilization, healthcare costs, greenhouse gas emissions, Spain, retrospective cohort, Impact, Initiation

Patients were excluded if they had incomplete data, acute infection or inflammatory conditions, autoimmune disease or another concurrent malignancy. They received chemotherapy alone (n=31), pembrolizumab plus chemotherapy (n=39), or atezolizumab plus chemotherapy (n=50), with treating oncologists making treatment decisions according to institutional clinical practice guidelines. The three groups did not differ significantly in baseline age, sex, smoking status or PD-L1 expression.

Tumor response was evaluated using RECIST version 1.1, while pulmonary function was assessed by forced expiratory volume in 1 second as a percentage of predicted value. Blood was collected on day 10 after the sixth treatment cycle between 9:00 and 10:00 a.m. Serum IL-6 was measured with an enzyme-linked immunosorbent assay, for which the reported detection range was 4.69–300 pg/mL and sensitivity was 2.8 pg/mL.

Patients were also assessed with routine blood counts, including hemoglobin, platelet count and neutrophil-to-lymphocyte ratio (NLR). Response distributions differed significantly among the treatment groups (p < 0.001). Progressive disease occurred in 48.4% of the chemotherapy group, 15.4% of the pembrolizumab group and 8.0% of the atezolizumab group.

Objective response, comprising complete or partial response, was reported in 16.1%, 61.5% and 60.0% of the respective groups. Disease control, defined as complete response, partial response or stable disease, was 51.6%, 84.6% and 92.0%, respectively. These were descriptive comparisons in nonrandomized treatment groups and do not establish comparative treatment efficacy.

Median post-treatment IL-6 concentrations also differed by treatment group: 16.5 pg/mL with chemotherapy, 12.5 pg/mL with pembrolizumab plus chemotherapy and 10.0 pg/mL with atezolizumab plus chemotherapy (p < 0.001). When patients were grouped by response, those with complete or partial response had a median IL-6 concentration of 9.23 pg/mL, compared with 15.7 pg/mL among those with stable or progressive disease (p < 0.001). These values were group medians with interquartile ranges, rather than average concentrations.

Receiver operating characteristic analysis estimated the ability of post-treatment IL-6 to discriminate progressive disease from non-progressive disease, with an area under the curve of 0.961 (95% confidence interval, 0.909–0.988). A threshold above 15.5 pg/mL had a reported sensitivity of 91.6% and specificity of 96.0%. This was an in-sample analysis in the treated cohort, and the reported performance has not established IL-6 as a validated clinical test.

Multivariable logistic regression retained an association between IL-6 and progressive disease. For each 1 pg/mL increase in IL-6, the adjusted odds ratio for progression was 1.72 (95% confidence interval, 1.34–2.21; p < 0.001). The NLR was associated with progression in the univariate analysis, with an odds ratio of 3.00 per one-unit increase (95% confidence interval, 1.88–4.80; p < 0.001), but it was not independently associated after adjustment (adjusted odds ratio 1.39; 95% confidence interval, 0.79–2.44; p=0.24).

Platelet count and FEV1 as a percentage of predicted also were not independently associated with progression. The findings are observational and do not establish that elevated IL-6 causes progression, that IL-6 is a cause-specific marker, or that measuring it would improve clinical decisions. The study did not assess longitudinal changes in IL-6, and the sample of 120 patients may limit subgroup analyses and generalizability.

All participants had COPD, and the results came from two Iraqi oncology centers, so applicability to patients without COPD or to other health systems requires assessment. The authors stated that the findings require confirmation in larger prospective longitudinal studies before IL-6 can be incorporated routinely into risk stratification or used to guide treatment decisions.

Subject of Research: Post-treatment serum IL-6 and progression in advanced NSCLC with COPD

Article Title: Post-treatment serum interleukin-6 is independently associated with disease progression in patients with advanced non-small cell lung cancer and coexisting COPD: a multicenter real-world cohort study

Article References: Kareem, A. H., Mohammed, S. I., & Shihad, A. A. (2026). Post-treatment serum interleukin-6 is independently associated with disease progression in patients with advanced non-small cell lung cancer and coexisting COPD: a multicenter real-world cohort study. Pharmacia, 73, Article e194159. https://doi.org/10.3897/pharmacia.73.e194159

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e194159

Keywords: NSCLC, COPD, interleukin-6, disease progression, chemotherapy, immune checkpoint inhibitors, observational cohort, risk stratification, Post-treatment, serum, independently, associated

The work targets a medically important but computationally difficult structure. Pulmonary fissures divide the lungs into distinct lobes, and their integrity can influence assessment of collateral ventilation before bronchoscopic lung-volume reduction procedures involving endobronchial valves. Incomplete fissures can permit gas and inflammation to move between adjacent lung regions, undermining the intended effect of valve-based treatment. Fissure detection also has roles in lesion localization and analysis of pulmonary diseases. Yet fissures often appear as faint, curved sheets with only one- or two-pixel-wide boundaries in CT imagery. In diseased lungs they may be deformed, interrupted or physically difficult to distinguish, making a tool that merely traces visible edges potentially unreliable.

Earlier computational approaches pursued this task with line-enhancement filters, ridge operators, derivative-based methods, anatomical atlases and watershed transformations. The study identifies two limitations associated with many deep-learning systems. First, deep networks commonly display a spectral bias, converging faster on low-frequency structures such as overall organ shapes than on high-frequency discontinuities such as fissure edges. The authors also cite evidence that multi-head self-attention can function as a spatial low-pass filter, attenuating fine signals and contributing to oversmoothing in deeper layers. Second, conventional Transformer attention has quadratic computational cost with respect to the number of tokens, creating a bottleneck for high-resolution three-dimensional volumes and encouraging compromises between spatial detail and long-range context.

CFT-Triplet addresses these constraints with a block that combines three kinds of information rather than simply stacking separate CNN and Transformer modules. Its Textural Branch uses cascaded residual convolutional units to retain local spatial patterns and edge information. Its Contextual Branch employs bidirectional Mamba2, a state-space model designed to model long-range dependencies with linear computational complexity. The Mamba2 configuration processes features in forward and reverse sequences and combines them through element-wise addition, allowing each direction to contribute to a global representation of anatomical continuity. Rather than operating as three independent branches, the Contextual and Frequency components are connected in series, with spectral refinement applied after contextual modeling.

The Frequency Branch is intended specifically to recover boundary information that may be weakened during global feature aggregation. Each directional feature stream passes through a learnable weighted fast Fourier transform block for spectral filtering and a multilayer perceptron for channel mixing. A learnable channel-wise parameter then balances the refined forward and backward features. The authors describe the effect as adaptive bandpass filtering: their feature-map analysis indicated that mid-to-high-frequency components were amplified without introducing extreme high-frequency noise. A separate Gate-Net fusion layer combines this sharpened global representation with the parallel Textural Branch. The gate, generated by two three-dimensional convolutional layers, a ReLU activation and a sigmoid function, spatially recalibrates the two streams so that the network can favor anatomical continuity in homogeneous regions and fine detail near boundaries.

The network was implemented as a hierarchical three-dimensional encoder-decoder operating on input patches measuring 160 by 160 by 160 voxels. The encoder reduces spatial resolution in five stages while increasing feature channels from 48 to 768. A bottleneck at 5 by 5 by 5 consolidates abstract features, and the decoder restores resolution through transposed convolutions, encoder skip connections and additional CFT-Triplet blocks. A scale-aware mixture-of-experts mechanism combines predictions from four decoder stages. Intermediate experts, with resolutions from 10 to 80 voxels per side, contribute differently to coarse shape and fine boundary detection. Their probabilities are resized, softmax-normalized and combined using instance-specific weights generated by global average pooling, a multilayer perceptron and softmax normalization. The training objective combined Tversky loss, which penalized false negatives more heavily, with weighted binary cross-entropy, which addressed the dominance of background voxels.

The retrospective dataset comprised 400 chest CT scans selected from 500 cases collected at Shandong Provincial Chest Hospital between June 2014 and November 2020. One hundred scans were excluded because of motion or metallic artifacts, incomplete lung coverage, unsuitable slice thickness or resolution, or severe pathology that obliterated the fissure anatomy. The remaining cases were divided at the patient level into 320 training scans, 40 validation scans and 40 test scans, a design intended to prevent data leakage. Testing therefore involved 40 held-out scans, not all 400 scans in the dataset. The scans came from Siemens, Philips and GE Medical Systems systems, with slice thicknesses of 0.625 to 1.25 millimetres and tube voltages of 100 to 120 kVp. Two experienced radiologists independently annotated fissures at voxel level, after which discrepancies were resolved in double-blind review by a senior specialist.

CFT-Triplet outperformed every comparator under a protocol that retrained all models with the same data splits, loss functions and hardware. Conventional CNN systems including U-Net, V-Net and Attention U-Net produced Dice scores of 78.85% to 81.15% and relatively high Betti number errors of 1.45 to 1.85, indicating more broken or fragmented predictions. Transformer models showed better continuity in the reported comparisons but were less precise at thin boundaries; nnFormer, for example, reached a Dice score of 83.92% and a normalized surface Dice of 86.85%. The Mamba-based U-Mamba and SegMamba-V2 performed better still. CFT-Triplet achieved 88.62% Dice, 88.18% precision, 92.15% normalized surface Dice at a one-millimetre tolerance and a Betti number error of 0.300. Its Dice improvement over SegMamba-V2 was associated with a Wilcoxon signed-rank p-value of 0.0083, while all reported comparisons met the study’s threshold of p below 0.05.

Ablation experiments supported the contribution and ordering of the model’s components. A texture-only encoder-decoder reached 80.45% Dice and a Betti number error of 1.650. Adding bidirectional Mamba2 raised Dice to 85.15% and reduced the topological error to 0.450. Arranging the Frequency Branch after contextual processing produced 87.50% Dice, 89.50% normalized surface Dice and a Betti number error of 0.350, outperforming parallel and frequency-first arrangements. Adding the multi-scale mixture of experts produced the full model’s 88.62% Dice and 0.300 Betti number error. Efficiency profiling at a 96-cubic-voxel input found 221.70 billion floating-point operations, 76 milliseconds of inference time and 9.4 gigabytes of GPU memory on one NVIDIA A100, compared with 240.20 billion operations, 135 milliseconds and 14.8 gigabytes for nnFormer and 328 billion operations, 112 milliseconds and 12.5 gigabytes for Swin UNETR.

The findings remain bounded by the study’s design. It was a retrospective evaluation on one private institutional dataset, and the model was tested on only 40 held-out cases, so performance in unselected hospitals, populations or scanning protocols is not established. The authors also reported that the system could struggle when severe emphysema had physically destroyed the fissure boundaries, causing its contextual branch to estimate separations that differed slightly from annotated pseudo-boundaries. The research therefore demonstrates an algorithmic advance rather than a clinical trial: it shows that a deliberately engineered combination of local texture, efficient global context and explicit frequency refinement improved quantitative fissure detection under the tested conditions. The findings do not establish improved patient selection, treatment planning or clinical outcomes.

Subject of Research: Retrospective evaluation of CFT-Triplet for three-dimensional pulmonary fissure segmentation in chest CT scans

Article Title: CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection

Article References: Xu, L., Jiang, Y., Tao, R., Li, N., Chen, R., Su, C., Li, G., & Tang, F. (2026). CFT-Triplet: integrating contextual, frequency and textural features for fine-grained pulmonary fissure detection. Frontiers in Artificial Intelligence, 9, Article 1817367. https://doi.org/10.3389/frai.2026.1817367

Image Credits: AI Generated

DOI: 10.3389/frai.2026.1817367

Keywords: pulmonary fissures, chest CT, medical AI, CFT-Triplet, Mamba2, frequency-domain learning, image segmentation, topological continuity, COPD, integrating, contextual, frequency

He praises the investigators for restricting their analysis to lifetime nonsmokers of tobacco while identifying two central weaknesses: chronic bronchitis was included in the definition of COPD, and asthma was not necessarily confirmed through objective testing. Restricting the study population to people who had never smoked tobacco was, in Tashkin’s view, an important design choice. Tobacco is a major risk factor for COPD and an important contributor to asthma morbidity, so including people with a history of tobacco use would have complicated efforts to distinguish a possible cannabis association from the effects of concomitant smoking.

The letter also notes that the investigators included very large numbers of recent cannabis users in the BRFSS survey. This restriction addressed one important source of confounding, but it did not resolve the problems created by how respiratory conditions were identified in the available data. The first concern involves the study’s definition of COPD.

Chronic bronchitis is not synonymous with COPD, the letter states, because COPD requires objective confirmation of airflow obstruction that is not fully reversible. The relevant spirometric criterion is a post-bronchodilator ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) below 0.70. By contrast, chronic bronchitis is identified by symptoms such as chronic cough and sputum.

Those symptoms are common among cannabis smokers who do not have COPD. Including chronic bronchitis within the study’s COPD definition could therefore produce an apparent association between cannabis use and COPD even among people who do not have objectively confirmed airflow obstruction. A similar issue applies to the asthma analysis.

The letter observes that asthma is often diagnosed on the basis of symptoms, including frequent wheezing and cough, without objective confirmation through spirometric evidence of reversible bronchospasm or evidence of bronchospasm provoked by bronchial challenge. If the survey-based classification cannot distinguish cannabis-associated respiratory symptoms from symptoms used to diagnose asthma, the reported association between cannabis use and asthma may partly reflect symptom overlap rather than confirmed disease. The absence of self-reported spirometry findings in the BRFSS telephone survey is therefore relevant to how both findings should be understood.

This critique does not establish that inhaled cannabis has no relationship to asthma or COPD, nor does the letter report new clinical outcomes. Instead, it focuses on measurement in a cross-sectional survey of self-reported information. The source study was large and its restriction to lifetime tobacco nonsmokers strengthened its attempt to address tobacco-related confounding, but the inclusion of chronic bronchitis in the COPD definition and the reliance on symptoms without objective respiratory testing limit the conclusions that can be drawn.

The letter’s central position is that the survey’s reported associations should not be treated as equivalent to diagnoses confirmed by physiological testing. A respondent with cough, sputum or wheezing may report symptoms that resemble chronic bronchitis or asthma without meeting the accepted clinical criteria for either condition, making cautious interpretation essential to the study’s scientific meaning.

Subject of Research: Interpretation of survey associations among inhaled cannabis users, asthma and COPD

Article Title: Inhaled Cannabis, Asthma, and Chronic Obstructive Pulmonary Disease: a Population-Based Cross-Sectional Study of n = 379,049: Letter to the Editor

Article References: Tashkin, D. P. (2026). Inhaled Cannabis, Asthma, and Chronic Obstructive Pulmonary Disease: a Population-Based Cross-Sectional Study of n = 379,049: Letter to the Editor. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10745-4

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10745-4

Keywords: inhaled cannabis, asthma, COPD, chronic bronchitis, respiratory symptoms, airflow obstruction, spirometry, BRFSS, cross-sectional study, research methods, Inhaled, Cannabis

One of the headline studies examines a question that has long troubled asthma specialists: whether empiric treatment with chronic proton pump inhibitors, medications routinely prescribed to suppress stomach acid, might actually worsen outcomes in patients with difficult-to-treat asthma. Using a propensity-matched United States cohort design, investigators analyzed biologic-treated patients with difficult-to-treat asthma and found that chronic proton pump inhibitor use was associated with an increased rate of exacerbations. The study does not establish causation, but the association is striking enough to prompt a reevaluation of a common prescribing pattern, particularly in a population already burdened by frequent flare-ups and heavy medication use.

The mechanistic rationale for caution is plausible. Proton pump inhibitors alter gastric pH, which can influence airway inflammation through microaspiration and changes in the microbiome, and prior observational work has suggested links between acid suppression and respiratory infections. In patients whose asthma is already difficult to control and who are receiving biologic therapy, any additional factor that tips the balance toward exacerbation carries clinical weight. The propensity-matching approach used in the study helps control for confounding by indication, since patients prescribed acid suppression often differ systematically from those who are not, but the authors and meeting organizers emphasize that the findings are associative and warrant prospective testing.

A second asthma-adjacent study shifts attention to chronic obstructive pulmonary disease with type 2 inflammation. Mepolizumab, a monoclonal antibody that blocks interleukin-5 and thereby reduces eosinophilic airway inflammation, has an established role in severe eosinophilic asthma. Pooled results from phase 3 randomized trials presented at the meeting indicate that mepolizumab reduces systemic corticosteroid utilization in patients with COPD and evidence of type 2 inflammation. This matters because chronic oral corticosteroid exposure drives a cascade of harms, including osteoporosis, diabetes, weight gain, and increased infection risk, and clinicians have long sought alternatives for the subset of COPD patients with eosinophilic biology.

The pooled analysis aggregates data across multiple phase 3 randomized trials, strengthening statistical power and allowing subgroup patterns to emerge that single trials might miss. For a disease as heterogeneous as COPD, identifying the eosinophilic, type 2 inflammatory phenotype as a treatment-responsive subgroup represents a shift toward precision medicine in an area where broad-spectrum bronchodilation has historically dominated. The results do not suggest mepolizumab for all COPD patients; rather, they support biomarker-guided selection, with blood eosinophil counts and other markers of type 2 inflammation serving as the gatekeepers to biologic therapy.

Bronchiectasis research at the meeting introduces a deceptively simple clinical tool: the color of a patient’s sputum as reported by the patient. In a post hoc analysis from the ASPEN trial, investigators examined whether patient-reported sputum color correlates with objective measures of airway inflammation, specifically neutrophil serine proteases, and with exacerbation risk. The findings suggest that the yellow or green discoloration long noted by clinicians at the bedside reflects real biochemical activity in the airways, since neutrophil-derived enzymes such as myeloperoxidase and neutrophil elastase impart the characteristic green hue through oxidative chemistry involving heme groups.

The ASPEN trial post hoc analysis is notable because it links a subjective, zero-cost patient report to molecular markers and clinical outcomes in a large trial population. If sputum color tracks with neutrophil serine protease activity and predicts exacerbations, it could serve as a practical triage signal in clinics and telemedicine encounters, flagging patients who need intensified anti-inflammatory or antimicrobial treatment before objective laboratory results return. The analysis is post hoc, meaning the endpoint was not the trial’s primary design goal, so the association requires confirmation in prospective studies, but the clinical logic is compelling and the implications for low-resource settings are considerable.

Critical care presentations tackle two of the most consequential questions in intensive care. The first applies machine learning to the problem of extubation failure, the situation in which a patient is removed from mechanical ventilation only to deteriorate and require reintubation within hours or days. Traditional weaning parameters, such as the rapid shallow breathing index and spontaneous breathing trial performance, have limited predictive power, and extubation failure carries significant mortality and morbidity penalties. In an analysis of the MIMIC-IV database, a large publicly available repository of intensive care unit records from Beth Israel Deaconess Medical Center, investigators trained machine learning models to predict extubation failure using features that extend beyond conventional weaning parameters.

The MIMIC-IV analysis exemplifies the current wave of clinical machine learning, in which high-dimensional electronic health record data, including vital signs, laboratory values, medication exposures, and ventilation settings, are mined for patterns invisible to single-parameter rules. Models of this kind can integrate trajectory information, capturing how a patient’s respiratory mechanics evolve over hours rather than relying on a single snapshot. The critical caveats are familiar: retrospective models trained on a single institution’s data risk overfitting and degraded performance on external populations, and algorithmic predictions must be validated prospectively and integrated thoughtfully into clinician decision-making. Still, the direction is clear, and the meeting’s inclusion of this work signals growing institutional interest in augmenting, not replacing, bedside judgment.

The second critical care study addresses telemedicine in the intensive care unit, evaluating tele-ICU implementation and program maturation in urban safety net hospitals through an 18-month multisite interrupted time-series analysis. Safety net hospitals serve disproportionately disadvantaged populations and often operate with constrained staffing, making them ideal test beds for remote intensivist support. Interrupted time-series design is among the strongest quasi-experimental methods available for evaluating health system interventions when randomized assignment is impractical, comparing outcome trajectories before and after implementation while accounting for secular trends. The 18-month horizon also allows the investigators to distinguish early implementation effects from the maturation phase, when teams adapt workflows and trust in the remote system develops.

Tele-ICU programs connect bedside teams with remote critical care specialists who monitor patients, review data, and advise on management around the clock. Evidence on tele-ICU effectiveness has been mixed across prior studies, with some large implementations showing mortality benefits and others showing null results, often attributed to differences in how the programs intervene rather than whether they exist. The new multisite analysis in safety net hospitals adds an equity dimension to this literature, since these institutions care for patients who historically experience worse critical care outcomes. The maturation finding, if it shows improving trajectories over time, would echo prior observations that tele-ICU benefits accrue gradually as integration deepens.

Interstitial lung disease research at the meeting advances two complementary frontiers. The first is noninvasive sphingolipid profiling, which distinguishes idiopathic pulmonary fibrosis from fibrotic hypersensitivity pneumonitis. These two fibrotic lung diseases can be difficult to differentiate clinically and radiographically, yet they carry different prognoses and treatment pathways, including the eligibility landscape for antifibrotic therapy and the importance of antigen avoidance in hypersensitivity pneumonitis. Sphingolipids, a class of lipid signaling molecules involved in cell proliferation, apoptosis, and inflammatory regulation, have emerged as biomarker candidates in fibrotic disease, and a blood-based profiling approach could spare patients from invasive surgical lung biopsy while accelerating diagnostic clarity.

The second interstitial lung disease study connects telomere biology to imaging. Shorter telomere length, a marker of cellular aging and replicative stress, is a recognized risk factor for pulmonary fibrosis, and telomere-related gene mutations are implicated in familial forms of the disease. The new research reports that shorter telomere length is associated with automated detection of usual interstitial pneumonia on imaging in patients with pulmonary fibrosis. Usual interstitial pneumonia is the histopathologic and radiologic pattern characteristic of idiopathic pulmonary fibrosis, and automated detection algorithms are increasingly capable of quantifying this pattern on high-resolution computed tomography. The association suggests that telomere attrition and the radiologic fingerprint of fibrosis are linked, potentially refining risk stratification in a disease where early identification changes treatment eligibility.

Lung cancer screening, one of the most consequential public health interventions in thoracic medicine, is the subject of a national gap analysis quantifying deficits in awareness, communication, and uptake. Low-dose computed tomography screening reduces lung cancer mortality in high-risk individuals, yet uptake in the United States remains persistently low, with eligible individuals often unaware of their eligibility or never receiving a recommendation from a clinician. The new analysis quantifies these deficits nationally, dissecting where the screening pipeline fails, from public awareness through clinician communication to actual completion of imaging. The framing matters because each stage of the pipeline represents a distinct intervention target, from mass media campaigns to electronic health record prompts that flag eligible patients during routine visits.

Taken together, the CHEST 2026 abstracts portray a specialty in transition, moving from one-size-fits-all approaches toward phenotype-guided therapy, from subjective bedside impressions toward molecular and algorithmic validation, and from fragmented care toward system-level interventions that reach underserved populations. The biologic era is expanding from asthma into COPD and bronchiectasis, machine learning is pressing against the limits of traditional critical care parameters, and lipidomics and telomere biology are reshaping the diagnosis of fibrotic lung disease. Meeting organizers note that all research presented at the meeting is available on the journal CHEST website, and the society emphasizes that the abstracts represent preliminary findings that will inform, but not replace, the peer-reviewed literature and clinical guidelines that follow.

Subject of Research: Research highlights from CHEST 2026 Annual Meeting

Article Title: Research highlights from CHEST 2026 Annual Meeting

Article References: Research highlights from CHEST 2026 Annual Meeting. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: CHEST 2026, pulmonary medicine, critical care, asthma, COPD, bronchiectasis, pulmonary fibrosis, lung cancer screening, tele-ICU, machine learning, Research, highlights

The device, described in a recent paper in Frontiers in Medical Engineering, is the brainchild of Victoria Ribeiro Rodrigues, Lizuannette Mejia, Rafael G. Zucchi, Paul W. Davenport, and Nicholas J. Napoli, working across the university’s Human Informatics and Predictive Performance Optimization (HIPPO) Lab and the Department of Physiological Sciences. Their goal was ambitious: to create a single apparatus capable of applying both static and dynamic loads to the chest wall and abdomen, with precise, reproducible, and independently adjustable force levels. Existing methods, they argue, have fallen short on all these fronts, forcing researchers to choose between crude approximations that lack quantitative feedback or elaborate setups that cannot transition between restriction types.

At the heart of the problem is a fundamental distinction between two kinds of restriction. Static restriction immobilizes the chest wall entirely, regardless of how hard a person tries to breathe, mimicking conditions such as external bracing or severe mechanical constraint. Dynamic restriction, by contrast, applies a constant resistive load that allows movement only when the breathing muscles generate sufficient force to overcome it, a scenario that better reflects the challenges faced by people with chronic obstructive pulmonary disease (COPD), jet pilots enduring high g-forces, or race car drivers under sustained acceleration. Prior devices have typically addressed one or the other, but never both within a single, instrumented platform.

The University of Florida team’s solution is a wooden frame structure, roughly 48 inches tall and 33 inches wide, that surrounds a seated participant. Two middle boards, one positioned over the chest and one over the abdomen, slide along four rods connecting a padded front compression surface to a rear support board. Each middle board carries a vinyl strapping band, three feet long and eight inches wide, that wraps around the participant’s torso and secures with Velcro. A ratchet gear mechanism tightens the bands, pulling them snug against the body, while an adjustable width system of sliding wooden blocks ensures the bands conform to participants of different sizes. The vinyl material is deliberately non-stretchable, preventing any unintended give that could confound measurements.

What elevates the device beyond its predecessors is its instrumentation. Two Linear Variable Differential Transducers, or LVDTs, supplied by Omega, measure the horizontal displacement of the chest wall and abdomen during breathing, capturing even subtle changes in movement patterns. Pressure sensors, built around Millar Mikro-Cath pressure catheters inserted into air bladders filled with exactly 60 milliliters of air, monitor the force exerted by the bands on the chest and abdomen. Before each trial, the catheters are calibrated according to manufacturer guidelines, and a live data feed allows researchers to verify that the applied load matches the target pressure, tightening the bands further if the baseline falls short.

The transition between static and dynamic modes is elegantly simple. In static mode, four shaft collars are positioned and tightened on the rods, locking the middle boards in place and preventing any forward movement regardless of the participant’s effort. In dynamic mode, the collars are removed and constant force springs, flat strips of spring material coiled into cylinders, are mounted on the backboard and connected to the middle boards via carabiners. Unlike conventional compression springs, these provide a steady force throughout their range of motion, reaching full strength after being stretched to 1.25 times their diameter. This allows the participant to move the boards slightly while maintaining a consistent resistive load, simulating the kind of graded restriction encountered in real-world scenarios.

To validate the device, the team recruited six healthy, non-smoking volunteers, four males and two females, with a mean age of 24 years and a mean body mass index of 25.56 kilograms per square meter. Participants underwent pulmonary function testing under three conditions: baseline without restriction, static restriction, and dynamic restriction with a load of 45 kilograms. The tests measured forced expiratory volume in one second (FEV1) and forced vital capacity (FVC), following American Thoracic Society and European Respiratory Society acceptability criteria. Respiratory data, including airflow and mouth pressure, were recorded using a pneumotach connected to a mouthpiece and a two-way non-rebreathing valve.

The results were striking. Under both static and dynamic restriction, FEV1 and FVC dropped significantly compared to baseline, confirming that the device successfully induces physiologically meaningful restriction. FVC declined by 20.8 percent under dynamic loading and 28.2 percent under static loading, while FEV1 fell by 21.6 percent and 28.2 percent respectively. These reductions align closely with average decreases reported in prior chest wall strapping studies, which typically report FVC reductions of around 25.1 percent and FEV1 reductions of 24.9 percent. Additional metrics, including inspiratory volume, inspiratory time, peak inspiratory airflow, and peak inspiratory pressure, also showed significant differences across conditions, with participants adapting their breathing patterns under load by taking shallower, longer breaths that reduce the instantaneous work of breathing.

Displacement data from the LVDTs provided further confirmation of the device’s capabilities. During static trials, chest and abdominal movement was virtually zero, validating the rigid, non-yielding nature of the restriction. In dynamic trials, displacement reached approximately 0.5 centimeters, demonstrating that the device permits measurable movement under load. Pressure variability tests, conducted across three repeated trials for each condition, showed consistent mean pressures: in the static condition, minimum chest pressures ranged from 3.18 to 3.41 kilopascals with standard deviations between 0.17 and 0.22, while minimum abdominal pressures ranged from 2.70 to 2.96 kilopascals. In the dynamic condition, pressures were similarly reproducible, confirming that the device can deliver adjustable and repeatable loads across participants and sessions.

The implications extend well beyond the laboratory. The researchers envision applications in studying respiratory diseases such as asthma and cystic fibrosis, where chest wall mechanics play a critical role in disease progression. The device could also illuminate the physiological challenges faced by military personnel wearing body armor, firefighters in heavy gear, or astronauts and deep-sea divers operating under unusual pressure conditions. Because the apparatus allows independent restriction of the chest and abdomen, it opens new avenues for understanding how each region contributes to breathing patterns and how the body adapts when one or both are compromised. The team also suggests the platform could be extended to investigate cognitive function, muscle fatigue, and blood circulation under restricted breathing, domains where the interplay between respiratory mechanics and broader physiology remains poorly understood.

Looking ahead, the researchers acknowledge that their validation was conducted in a young adult sample, and that the effects of chest wall restriction may be amplified in older individuals, whose chest walls are stiffer due to calcified cartilage and vertebral deformities, and whose lungs have lost elastic recoil. Future studies, they argue, should include broader age ranges and populations with respiratory diseases, with careful attention to load levels that avoid triggering bronchoconstriction in vulnerable participants. Refinements to accommodate extreme body types and adjustable spring resistance for those with compromised pulmonary function could further expand the device’s reach. For now, the device stands as a versatile new tool in the growing effort to understand, model, and ultimately mitigate the respiratory challenges that arise when the simple act of breathing becomes a battle against constraint.

Subject of Research: Respiratory mechanics and biomedical engineering

Article Title: Chest wall restriction device for modeling respiratory challenges and dysfunction

Article References: Ribeiro Rodrigues, V., Mejia, L., Zucchi, R. G., Davenport, P. W., & Napoli, N. J. (2025). Chest wall restriction device for modeling respiratory challenges and dysfunction. Frontiers in Medical Engineering, 3, Article 1560136. https://doi.org/10.3389/fmede.2025.1560136

Image Credits: AI Generated

DOI: 10.3389/fmede.2025.1560136

Keywords: chest wall restriction, respiratory mechanics, breathing dysfunction, pulmonary function testing, biomedical engineering, static and dynamic loads, COPD, extreme environments, Chest, wall, restriction, device

The study, conducted at the University Clinic of Pulmonology and Allergology in Skopje between May and December 2025, enrolled 70 adults hospitalized with acute exacerbations of COPD. All patients received empirical intravenous antimicrobial therapy on their first day in hospital, following institutional protocols based on European Respiratory Society guidelines for lower respiratory tract infections. Before the first antibiotic dose was given, researchers collected sputum and bronchoalveolar lavage samples and analyzed them in parallel using conventional microbiological culture and the BioFire FilmArray Pneumonia Panel Plus, a multiplex polymerase chain reaction (PCR) assay capable of detecting 18 bacterial targets, nine viral targets, and seven antimicrobial resistance genes in a single run.

The diagnostic yield difference was striking. Respiratory pathogens were identified in 45 of the 70 patients (64.3 percent), and multiplex PCR detected a range of respiratory viruses—influenza A and B, respiratory syncytial virus, human rhinovirus/enterovirus, human coronavirus OC43, and human metapneumovirus—that conventional culture simply cannot routinely identify. Influenza A virus and respiratory syncytial virus were the most frequently detected pathogens, each found in ten patients, followed by Pseudomonas aeruginosa and human rhinovirus/enterovirus in nine patients each. Culture retained an important niche, however: fungal pathogens such as Candida species and Trichosporon species were detected exclusively by conventional methods, underscoring that the two approaches are complementary rather than interchangeable.

What set this study apart was the role of the clinical pharmacist. Rather than acting as a peripheral advisor, the pharmacist was directly involved in running the molecular diagnostics laboratory and interpreting the PCR results, then translating those findings into patient-specific recommendations within the antimicrobial stewardship workflow. Once PCR results became available, therapeutic modifications were typically implemented within the first 24 hours. Antibiotic discontinuation was recommended in 44 patients (62.8 percent), targeted antimicrobial optimization was performed in nine patients (12.9 percent), and empirical therapy was maintained without change in 17 patients (24.3 percent).

The specific interventions illustrate how molecular results translate into prescribing decisions. When influenza A or B was detected, the pharmacist recommended initiating oseltamivir and stopping unnecessary antibiotics. For other isolated viral infections—including respiratory syncytial virus, rhinovirus/enterovirus, metapneumovirus, and coronavirus OC43—the recommendation was straightforward antibiotic discontinuation. In cases of viral-bacterial co-infection, empirical therapy was maintained or modified according to the detected pathogens. When Pseudomonas aeruginosa was identified, the pharmacist recommended switching from moxifloxacin to ceftazidime, a targeted change driven by the organism’s resistance profile.

Perhaps the most compelling example of the technology’s value came from a single patient in whom multiplex PCR detected Serratia marcescens together with the VIM (Verona integron-encoded metallo-β-lactamase) resistance marker—a carbapenemase gene of significant clinical concern. This detection prompted a switch from moxifloxacin to ciprofloxacin, demonstrating that rapid molecular diagnostics can inform antimicrobial choices well beyond simple pathogen identification, flagging resistance mechanisms early enough to shape therapy in real time.

On the outcome side, the median hospital stay was 12 days, with a range of 5 to 25 days. Laboratory markers of inflammation improved substantially by discharge: median C-reactive protein fell from 16.05 mg/L at admission to 3.0 mg/L, and leukocyte counts and lactate dehydrogenase levels also declined. Using point-biserial correlation analysis with Bonferroni correction for multiple comparisons, only one microbiological variable remained significantly associated with prolonged hospitalization: infection with human rhinovirus/enterovirus. Patients positive for this virus stayed a median of 20 days compared with 11 days for those without it, a difference confirmed by non-parametric sensitivity analysis.

The rhinovirus finding deserves careful interpretation. Only nine patients tested positive for human rhinovirus/enterovirus, and most detections occurred in the context of co-infection—five patients had concurrent bacterial pathogens such as Streptococcus pneumoniae, Pseudomonas aeruginosa, Escherichia coli, or Haemophilus influenzae, and two had additional viral co-detections. Only two patients had rhinovirus/enterovirus as a single pathogen. The longest hospitalization in the study, 25 days, occurred in a patient with combined respiratory syncytial virus, rhinovirus/enterovirus, and E. coli infection. This pattern suggests that the association may reflect the greater clinical complexity of mixed infections rather than an independent effect of rhinovirus alone, though previous research has shown that rhinovirus can enhance airway inflammation, impair antibacterial host defenses, and facilitate secondary bacterial infection in COPD.

The study has clear limitations that temper its conclusions. The single-arm observational design, without a comparator group receiving stewardship without PCR guidance, cannot establish the independent contribution of molecular diagnostics to outcomes. The single tertiary-care center and modest sample size limit generalizability, several pathogens were detected too infrequently for meaningful statistical analysis, and the study captured only in-hospital outcomes without long-term follow-up for mortality or readmissions. These caveats notwithstanding, the work provides real-world evidence from a setting where conventional culture remains the diagnostic cornerstone and advanced molecular infrastructure is still emerging—a context highly relevant to many low- and middle-income health systems.

The broader significance lies in what the model demonstrates about workflow integration. Pharmacist-led stewardship programs have previously been shown to improve antibiotic prescribing quality in COPD exacerbations, and multiplex PCR has been shown to accelerate pathogen detection in pneumonia. This study brings the two together, positioning the clinical pharmacist as the interpretive bridge between the molecular laboratory and the bedside. With nearly two-thirds of patients able to stop antibiotics based on PCR-guided recommendations, and with resistance markers detectable within hours rather than days, the approach offers a concrete template for how rapid diagnostics and stewardship expertise can be combined to curb unnecessary antimicrobial exposure in one of the most common reasons for hospital admission worldwide.

Subject of Research: Integration of multiplex PCR diagnostics into pharmacist-led antimicrobial stewardship for COPD exacerbations

Article Title: Clinical pharmacist-led multiplex polymerase chain reaction diagnostics as a tool for antimicrobial stewardship in acute exacerbations of chronic obstructive pulmonary disease

Article References: Nakovska, O. K., Mihajloska, E., Debreshlioska, A., Karkinski, D., Tatabitovska, A., Grozdanova, A., & Shuturkova, L. (2026). Clinical pharmacist-led multiplex polymerase chain reaction diagnostics as a tool for antimicrobial stewardship in acute exacerbations of chronic obstructive pulmonary disease. Pharmacia, 73, Article e203025. https://doi.org/10.3897/pharmacia.73.e203025

Image Credits: AI Generated

DOI: 10.3897/pharmacia.73.e203025

Keywords: COPD, multiplex PCR, antimicrobial stewardship, clinical pharmacist, respiratory viruses, antibiotic de-escalation, human rhinovirus, Pseudomonas aeruginosa, antimicrobial resistance, hospital length of stay, molecular diagnostics, Clinical

The research, coordinated by first authors Alex Kayongo, Theda Ulrike Patricia Bartolomaeus and Till Birkner, with Sofia K. Forslund-Startceva as senior author, enrolled 200 adults stratified by both HIV and COPD status. Crucially, 160 of these participants were followed for two years, allowing the team to move beyond a single snapshot and examine how airway microbial communities change over time. This longitudinal design matters because cross-sectional studies, which sample individuals at only one point, cannot distinguish stable disease-associated features from ordinary temporal fluctuation, a limitation that has hampered much of the previous microbiome literature in respiratory medicine.

Methodologically, the study stands out for the breadth of its integrated multi-omics framework. The researchers combined 16S rRNA gene profiling of sputum to characterise bacterial communities, quantification of bacterial outer membrane vesicles, which are small membrane-bound particles shed by bacteria that can carry inflammatory cargo, and detailed profiling of airway cytokines, the signalling molecules that orchestrate inflammation. On the host side, they deployed cytometry by time of flight, or CyTOF, to phenotype immune cells at high resolution, bulk transcriptomics of induced sputum, bronchoalveolar lavage and peripheral blood, and single-cell RNA sequencing of bronchoalveolar lavage cells, which was then used to guide computational deconvolution of cell-type proportions in bulk samples.

Perhaps the most striking finding is what the team did not find. Contrary to expectations, sputum microbial communities were shaped predominantly by temporal ecological turnover, meaning that the composition of the airway microbiome changed substantially over time within individuals, rather than being primarily determined by HIV status, COPD status, or the combination of the two. Microbial diversity, microbiome instability, outer membrane vesicle burden and inferred airway cellular composition were largely preserved across the clinical groups. This suggests that the airway microbial ecosystem in this cohort is more resilient, or at least more variable in ways unrelated to disease, than many researchers had assumed.

Yet the study did not come up empty-handed. When the authors looked more closely, they identified disease-specific microbial signatures associated with HIV-associated COPD, indicating that particular bacterial taxa or community patterns do track with the combined condition even though the overall architecture of the microbiome does not. Alongside these microbial signatures, the team detected inflammatory transcriptional remodeling that was concentrated in induced sputum, the sample type most directly reflecting the airway environment. In other words, the host’s gene expression programs in the airways, rather than gross microbial composition, appear to be where the immunological fingerprint of HIV-associated COPD is most clearly written.

The emphasis on non-linear host-microbe interactions is central to the study’s conceptual contribution. Traditional analyses often test for simple linear associations between the abundance of a microbial taxon and a host measurement. Such approaches can miss relationships that only emerge above certain abundance thresholds, that depend on the presence of other microbes, or that vary across immune contexts. By applying integrated analyses designed to capture these selective and non-linear interaction networks, the researchers were able to link discrete microbial taxa with specific inflammatory, immune and transcriptional programmes, mapping a web of relationships that would have been invisible to simpler statistical models.

These findings carry substantial implications for how microbiome research in respiratory disease should be interpreted and designed. If temporal turnover dominates microbial variation, then single-time-point studies risk misattributing random ecological drift to disease. Conversely, if the most robust disease signals reside in host transcriptional responses and in selective, context-dependent interactions with particular taxa, then therapeutic strategies aimed at broadly reshaping the microbiome, such as indiscriminate antibiotics, may be poorly matched to the underlying biology. More targeted interventions, informed by the specific host-microbe networks identified here, become a more plausible long-term goal.

The study is also notable for its setting and its collaborative structure. Conducted in Uganda with clinical sites including Makerere University Lung Institute, Nakaseke General Hospital and the African Community Center for Social Sustainability, and with analytical partners in Berlin, Vienna, Graz, Heidelberg, London, Miami and Baltimore, the work addresses a genuine gap in global health research. Most large-scale airway microbiome studies have been conducted in high-income countries, and the ecology of the airway in African populations, where HIV prevalence, environmental exposures and prior infectious disease histories differ substantially, has been poorly characterised. The funding came from the US National Institutes of Health Fogarty International Center, the European and Developing Countries Clinical Trials Partnership supported by the European Union, Novartis Global Health, the German Research Foundation, the German Federal Ministry of Education and Research and the European Union’s Horizon 2020 programme.

For clinicians managing the growing population of people living with HIV who develop chronic lung disease, the study offers both reassurance and a caution. The relative preservation of microbial diversity and immune composition suggests that HIV-associated COPD in this cohort is not simply a state of catastrophic ecological collapse in the airways. At the same time, the identification of disease-specific microbial signatures and concentrated inflammatory remodeling in induced sputum points to measurable molecular changes that could, with further validation, serve as biomarkers for disease activity or treatment response. Because the inflammatory signal was strongest in the airway compartment itself, sputum-based monitoring may prove more informative than peripheral blood markers.

The authors note that the article was shared early to provide faster access to peer-reviewed, accepted research, with a final version of record to follow, and the work is published open access under a Creative Commons Attribution licence. As follow-up studies extend this framework to larger cohorts, longer follow-up periods and interventional settings, the central lesson of this research is likely to endure: understanding chronic lung disease in people living with HIV requires looking not just at which microbes are present, but at when they change, how they interact with host immunity in non-linear ways, and where in the airway the resulting inflammatory programs are actually expressed.

Subject of Research: Airway microbiome ecology and host immune interactions in HIV-associated COPD

Article Title: Microbial ecological instability and non-linear host interactions shape airway inflammation in HIV-associated COPD

Article References: Kayongo, A., Bartolomaeus, T. U. P., Hecker, J., Birkner, T., Vila, E., Ntayi, M. L., Markó, L., Löber, U., Olweny, G., Kyalo, E., Kyamulabi, D., Ndawula, J., Ssengooba, W., Nabatanzi, R., Kyobe, S., Nassali, F., Kigozi, E., Kalyesubula, R., Munana, R., … Forslund-Startceva, S. K. (2026). Microbial ecological instability and non-linear host interactions shape airway inflammation in HIV-associated COPD. Nature Communications. https://doi.org/10.1038/s41467-026-78400-4

Image Credits: AI Generated

DOI: 10.1038/s41467-026-78400-4

Keywords: HIV, COPD, airway microbiome, 16S rRNA profiling, outer membrane vesicles, CyTOF, single-cell RNA sequencing, cytokines, inflammation, multi-omics, Uganda, host-microbe interactions

The story of ESM1 began in 1996, when researchers first identified the molecule in a cDNA library derived from human umbilical vein endothelial cells. The gene sits on chromosome 5q11.2, spans roughly 12 kilobases, and encodes a signal peptide of 19 amino acids followed by a mature polypeptide of 165 amino acids. After the signal peptide is cleaved in the endoplasmic reticulum, the core protein undergoes O-glycosylation, receiving a linear dermatan sulfate chain at the serine residue at position 137. The finished product is a cysteine-rich molecule of about 50 kilodaltons, carrying an N-terminal epidermal growth factor-like domain and a C-terminal phenylalanine-rich region, each with distinct biological jobs.

That structural architecture matters functionally. The cysteine-rich domain is involved in blocking leukocyte adhesion and activation, while the phenylalanine-rich region promotes cancer cell proliferation and invasion. The dermatan sulfate chain binds pro-angiogenic factors, tying ESM1 to embryonic development and tumor progression. Beyond its structural roles, ESM1 promotes cell proliferation by accelerating the G1/S transition of the cell cycle through cyclin D1 and CDK4, drives metabolic reprogramming by stimulating fatty acid synthesis and the Warburg effect, inhibits autophagy and apoptosis, and promotes both endothelial-to-mesenchymal transition and epithelial-mesenchymal transition, processes central to fibrosis and cancer spread.

Perhaps the most puzzling feature of ESM1 is its dual relationship with inflammation. On one hand, the protein stimulates endothelial secretion of interleukin-8 and monocyte chemoattractant protein, loosens tight junctions to increase vascular permeability, and enhances monocyte adhesion under chronic intermittent hypoxia. On the other hand, it directly binds the integrin LFA-1, preventing the leukocyte adhesion molecule from engaging ICAM-1 and thereby blocking white blood cell migration into tissue. The review suggests three possible explanations for this Jekyll-and-Hyde behavior: different molecular mechanisms may dominate in different settings, the glycanated and non-glycanated forms of the protein may carry opposite functions, and the disease context itself, whether sepsis or acute lung injury, may determine which face of ESM1 prevails.

Molecularly, ESM1 sits at the hub of an elaborate signaling web. It participates in positive feedback loops with the epidermal growth factor receptor, in which EGFR activation drives ESM1 expression and ESM1 in turn promotes EGF binding to EGFR. It forms similar self-reinforcing circuits with the HGF/c-MET pathway and the VEGF-A pathway, the latter through its ability to bind fibronectin in the extracellular matrix and release stored VEGF-A to activate VEGFR-2. Additional pathways involving NF-κB, mTOR, ZEB1/PI3K/AKT, DLL4/Notch, and Wnt/β-catenin connect ESM1 to proliferation, angiogenesis, drug resistance, and immune evasion. Under intermittent hypoxia, the HIF-1α/VEGF pathway ramps up ESM1 production, a mechanism with direct relevance to sleep-disordered breathing.

In lung cancer, the leading cause of cancer-related death worldwide, ESM1 behaves as a tumor promoter. It drives proliferation, invasion, epithelial-mesenchymal transition, and chemoresistance while reshaping the tumor microenvironment by boosting pro-angiogenic factors and promoting endothelial lipid synthesis. In non-small cell lung cancer, the most prevalent histological subtype, ESM1 activates both the EGFR/ESM1 loop and an ESM1/HGF/c-MET circuit that fuels angiogenesis. It may also enhance the stemness and drug resistance of cancer stem cells through HIF-1α signaling and elevate long non-coding RNAs such as H19 and HULC. The authors note that whether additional pathways, including Wnt/β-catenin and DLL4/Notch, contribute in lung cancer remains unresolved.

The picture shifts in obstructive sleep apnea hypopnea syndrome, the most common sleep disorder globally. Serum ESM1 rises in patients, partly through downregulation of microRNA-181a-1, and falls after treatment. Working through the HIF-1α/VEGF pathway under intermittent hypoxia, elevated ESM1 increases vascular permeability, stimulates expression of the adhesion molecules ICAM-1 and VCAM-1, and strengthens monocyte binding to endothelial cells, collectively amplifying vascular inflammation. In pulmonary arterial hypertension, ESM1 levels are likewise elevated and appear to promote disease by inducing endothelial-to-mesenchymal transition and entering a positive feedback loop with TNF-α, in which each molecule spurs production of the other, worsening endothelial injury and vascular remodeling. The review cautions, however, that most PAH evidence comes from animal models and cell experiments rather than patient studies.

In the starkest contrast, ESM1 appears protective in acute lung injury and acute respiratory distress syndrome. There, the protein reduces neutrophil infiltration by inhibiting LFA-1/ICAM-1-dependent leukocyte migration, dampens secretion of TNF-α, interferon-γ, and interleukin-1β, restores mitochondrial respiratory function by reversing lipopolysaccharide-induced overactivation of the mitochondrial unfolded protein response, and helps repair the endothelial glycocalyx that maintains the pulmonary vascular barrier. Elevated endocan has even been proposed as an early marker of disease severity in ARDS. Yet the authors acknowledge an unresolved tension: given ESM1’s documented pro-inflammatory actions elsewhere, whether it might also promote inflammation in some phases of ALI/ARDS is still unknown.

The remaining respiratory diseases occupy murkier territory. In COPD, evidence points in conflicting directions: some studies suggest ESM1 protects against emphysema by enhancing the protective effects of HGF and VEGF, while others indicate it accelerates lung tissue injury through Fas/FasL-mediated apoptosis of structural cells. In COVID-19, elevated ESM1 correlates with severity and may promote thrombosis by activating leukocytes and platelets, but the relationship remains poorly characterized. In pneumonia, ESM1 shows anti-inflammatory effects and holds promise for distinguishing bacterial from viral infections and predicting severity, including in Mycoplasma pneumoniae pneumonia. Its roles in asthma and sarcoidosis, likely tied to microvascular inflammation and endothelial dysfunction, await proper definition.

What emerges from this comprehensive synthesis is a molecule of remarkable complexity, one whose effects cannot be summarized as simply good or bad. ESM1’s impact depends on its structural state, the signaling environment, and the specific disease at hand, which is precisely what makes it both scientifically fascinating and clinically treacherous. The Kunming team argues that decoding the mechanism behind ESM1’s dual inflammatory roles, clarifying its function in COPD, asthma, and pneumonia, and mapping the specific pathways connecting it to TNF-α are the critical next steps. If those puzzles are solved, targeting ESM1, whether to amplify its protective or suppress its damaging activities, could open a new therapeutic frontier spanning lung cancer, pulmonary hypertension, sleep apnea, and the acute lung injuries that fill intensive care units worldwide.

Subject of Research: The role and signaling mechanisms of the endothelial proteoglycan ESM1 in respiratory diseases

Article Title: The role and mechanism of endothelial cell-specific molecule-1 in respiratory diseases

Article References: Huang, L., Liu, X., Rao, Q., Zou, Y., Wen, Y., Arif, T., Zheng, Y., & Sun, S. (2026). The role and mechanism of endothelial cell-specific molecule-1 in respiratory diseases. Frontiers in Physiology, 17, Article 1914718. https://doi.org/10.3389/fphys.2026.1914718

Image Credits: AI Generated

DOI: 10.3389/fphys.2026.1914718

Keywords: ESM1, endocan, endothelial cells, lung cancer, pulmonary arterial hypertension, ARDS, COPD, obstructive sleep apnea, inflammation, angiogenesis, signaling pathways, metabolic reprogramming

The study, led by Vincent Mougin of the Karolinska Institutet together with collaborators including researchers at the Institute for Health Metrics and Evaluation, harnessed the extraordinary statistical infrastructure of the Swedish state. By linking the Total Population Register, the National Patient Register, the Cause of Death Register and the LISA labour market database, the team assembled a cohort of nearly 6.85 million unique individuals diagnosed between 2001 and 2023, contributing more than 196 million person-years of observation. That scale, and the near-complete population coverage of Scandinavian registers, allowed something no previous study had achieved: a harmonised, like-for-like comparison of income-related survival gaps across the entire spectrum of non-communicable disease.

The technical approach was as important as the scale. Rather than comparing raw survival rates — which would be hopelessly confounded, since low-income Swedes tend to be older, and differ in sex distribution and era of diagnosis — the researchers used flexible parametric survival models with regression standardisation. Restricted cubic splines captured the shape of the baseline hazard over time without forcing the data into proportional hazards assumptions, and standardisation produced marginal survival curves: estimates of what survival would look like if everyone in a cohort shared the same income level while keeping their actual age, sex and diagnosis year. Income itself was defined carefully, using five-year lagged, consumption-equivalised household disposable income ranked into quartiles within sex and birth-year strata, a technique designed to strip out short-term income shocks caused by illness itself.

The headline finding is stark in its uniformity. After standardisation, individuals in the bottom income quartile had lower ten-year survival than those in the top quartile for all 100 disease categories, and the confidence interval for the difference excluded zero in every case. For 37 conditions, the absolute gap exceeded ten percentage points. The largest per-person disparities clustered around smoking- and alcohol-related diseases: ten-year survival for other pharynx cancer was 34.2 percent among the poorest versus 58.2 percent among the richest — a 24-point chasm in a country where chemotherapy, surgery and radiotherapy are free at the point of use. Larynx cancer, lip and oral cavity cancer, chronic obstructive pulmonary disease, endocarditis and aortic aneurysm all showed gaps of more than 14 percentage points.

One especially striking pattern emerged in diseases with intermediate prognoses. For conditions where overall ten-year survival hovered between roughly 40 and 60 percent — a group dominated by cardiovascular disease — income acted almost as a switch. Ten years after an ischaemic heart disease diagnosis, the researchers note, a Swede in the top income quartile is more likely to be alive than dead, while someone in the bottom quartile is more likely to be dead than alive. The same grim arithmetic holds for hypertensive heart disease, ischaemic and haemorrhagic stroke, aortic aneurysm, prostate cancer and several others. The authors suggest this may reflect a mix of statistical floor and ceiling effects — survival differences are mechanically compressed where nearly everyone lives or nearly everyone dies — alongside the fact that these intermediate conditions are precisely where treatment quality, adherence and risk-factor management tip outcomes.

To express the gaps in a clinically intuitive metric, the team calculated ten-year restricted mean survival time, effectively the average number of years lived within a decade of diagnosis. Low-income patients with other pharynx cancer lost 1.90 years compared with high-income patients, larynx cancer patients 1.46 years, and COPD patients just over a year. But when the researchers scaled these per-person differences up to the population level, the picture inverted. Rare head and neck cancers, despite their enormous individual gaps, contributed relatively little to the national total because so few people are diagnosed. Instead, the greatest absolute burden came from humdrum, highly prevalent conditions: hypertension alone accounted for roughly 352,000 person-years of survival lost among low-income patients, with atrial fibrillation, stroke, heart failure and urinary tract infections close behind. In total, about 6.2 million person-years of survival were lost within ten years of diagnosis — the difference between what low- and middle-income patients actually experienced and a counterfactual in which they had enjoyed high-income survival trajectories.

Perhaps the most methodologically sophisticated part of the study tackled a deceptively simple question: are these gaps just the familiar income gradient in life expectancy showing through, or does income specifically change what happens after you are diagnosed? The researchers matched each diagnosed patient to five disease-free controls sharing the same birth year, sex and income quartile, then compared survival loss relative to those controls across income groups. For 73 of the 100 disease categories, the poorest patients lost significantly more survival time to their disease than the richest — a difference that persisted after netting out background mortality. This extends a logic familiar from deprivation-stratified relative survival analyses in cancer epidemiology, but applies it across cardiovascular, respiratory, neurological and mental health conditions, suggesting the pattern is not a cancer quirk but a general feature of illness in an unequal society.

Why does income still matter so much in a welfare state? The observational design cannot pin down mechanisms, but the authors sketch two non-exclusive pathways. First, lower income may worsen the course of disease after onset — through later presentation, differences in treatment, adherence to medication, management of comorbidities, and the practical costs of being ill, such as prescription charges, travel and lost earnings. Second, low-income patients may simply enter the register later, at a more advanced stage of disease, since cohort entry here marks first recorded specialist care rather than true disease onset. The breadth of the findings, spanning fast-moving cancers where early detection is everything and slow chronic diseases where long-term management dominates, suggests no single mechanism suffices. Upstream forces compound the problem: smoking and alcohol harm concentrate among the poor, financial insecurity feeds chronic stress, cheaper processed diets and low-control work add cardiovascular risk, and disadvantages accumulate within the same people across a lifetime.

The authors caution that their estimates are probably conservative. Older people living on modest pensions may be misclassified as low-income despite secure circumstances, diluting the measured association, and Sweden’s comparatively low inequality and strong safety nets likely mean the gaps would be wider in countries with higher out-of-pocket costs. Still, income inequality in Sweden has risen faster than in most OECD countries in recent decades, and the life expectancy gap between rich and poor has widened in parallel. For policymakers, the study offers a triage map: intervening on prevalent cardiovascular conditions such as hypertension and ischaemic heart disease would deliver the largest absolute reductions in survival inequality, while focused prevention and early detection for smoking- and alcohol-related cancers — including HPV-driven pharyngeal tumours — would benefit each affected person most. More broadly, the findings are a reminder that universal coverage removes the price tag on a hospital bed but not the many other ways that money buys health.

Subject of Research: Income-related survival disparities across 100 disease categories in Sweden

Article Title: Income-related differences in survival across disease categories in Sweden: a retrospective population-based register study

Article References: Mougin, V., Gray, A., Naghavi, M., Allebeck, P., Kinge, J. M., Wool, E. E., Weaver, N. D., Murray, C. J., & Agardh, E. E. (2026). Income-related differences in survival across disease categories in Sweden: a retrospective population-based register study. The Lancet Regional Health – Europe, 71, Article 101896. https://doi.org/10.1016/j.lanepe.2026.101896

Image Credits: AI Generated

DOI: 10.1016/j.lanepe.2026.101896

Keywords: health inequality, survival analysis, Sweden, income, non-communicable diseases, cardiovascular disease, cancer, COPD, universal healthcare, register study, life expectancy, epidemiology