Size Heterogeneity Research Articles

Multidimensional Environmental Drivers of Bamboo Species Richness on Subtropical Islands

Understanding the distribution patterns and driving mechanisms of bamboo species diversity on islands is essential for advancing knowledge of island ecosystem processes and informing strategies for bamboo resource conservation and management. This study utilized standardized major axis regression (SMA) to assess the effects of island area and isolation on bamboo species across 30 islands in Fujian, China. Furthermore, a partial least squares structural equation model (PLS-SEM) was constructed to explore the driving mechanisms underlying bamboo species richness. This analysis incorporated six key environmental factors—island size, isolation, shape, climate, development intensity, and habitat heterogeneity—spanning a total of 12 variables. The primary findings were as follows: (1) Eight genera and twenty-nine bamboo species were identified on Fujian islands. Species richness increased significantly with island area, consistent with the theory of area effects, while isolation had no significant impact on richness. (2) Different reproductive types exhibited distinct responses to environmental conditions. This was evident in the species–area relationship slopes (z-values): SR = 2.07; monopodial = 0.94; sympodial = 0.82; and polycyclic = 0.44. These variations highlight the ecological adaptability and functional traits of different reproductive strategies within island ecosystems. (3) Among the six environmental factors, island area exerted the greatest influence on species richness, underscoring its role as the primary driver of bamboo diversity and reproductive strategies. (4) Island area and isolation also impacted species richness indirectly through their effects on development intensity. In conclusion, the bamboo species richness and reproductive types on Fujian islands are primarily shaped by island area, followed by development intensity and habitat heterogeneity. In contrast, climate, island shape, and isolation play relatively minor roles. This study provides critical insights into the interplay of island area, isolation, shape, climate, development intensity, and habitat heterogeneity in shaping bamboo diversity. The findings offer a valuable foundation for bamboo resource conservation, island ecosystem management, and sustainable development.

The opportunities in implementing assistive technology in oral health care for individuals with sensory impairments: a systematic review.

People with sensory impairments (SI) face unique challenges in out-of-home care, especially in oral health (OH) care, compared to the general population. Various assistive technologies (ATs) and media are used to influence OH behaviors and outcomes for individuals with SI. This systematic review (SR) aimed to identify the types of ATs and assess their effectiveness for individuals with SI. A comprehensive search strategy was applied across Scopus, PubMed, Cochrane Library, ProQuest, and Scopus databases, using expert-validated keywords, with manual searches for relevant articles published from June 2013 to June 2023. The SR followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Eligible studies focused on the use of ATs as OH education tools for individuals with SI and assessed their impact on OH behavior and status. Eighteen of the 1298 identified studies were included in the data synthesis. ATs, such as images, software, multimedia, audio, video, audio-tactile performance, and combination methods, were effective for OH care in individuals with SI. However, this SR limitations include study heterogeneity in sample sizes, intervention types, and outcomes, as well as the exclusion of non-English studies. Oral health education using a combination of video training and audio-tactile performance is particularly effective for individuals with SI, engaging multiple senses for learning. Future research should focus on standardizing methodologies and incorporating larger sample sizes to enhance the efficacy of these technologies in improving OH care for individuals with SI. PROSPERO REG. NO.: CRD42023485523.

The Impact of Age on Second Language Learning

This research examines the correlation between age and second language acquisition (SLA), emphasizing the Critical Period Hypothesis (CPH) and age-related variations in phonology, grammar, and vocabulary acquisition. The results indicate that younger learners excel in achieving native-like pronunciation and implicit grammar, but adults exhibit advantages in explicit learning and vocabulary acquisition owing to cognitive maturity and metalinguistic awareness. The study underscores the limited validity of the Critical Period Hypothesis, indicating that second language acquisition results are shaped by biological, social, and environmental variables rather than strict age limitations. Practical consequences encompass the necessity for age-specific pedagogical approaches, early language acquisition initiatives, and continuous learning opportunities. Limitations, including a small sample size and cross-linguistic heterogeneity, are recognized, with suggestions for future study to investigate longitudinal effects, cross-linguistic disparities, and the incorporation of neuroscience into second language acquisition studies. By addressing these results, educators and policymakers may more effectively support different learner profiles and improve second language acquisition outcomes across all age groups.

Influence of the glycocalyx on the size and mechanical properties of plasma membrane-derived vesicles.

Recent studies have reported that the overexpression of MUC1 glycoproteins on cell surfaces changes the morphology of cell plasma membranes and increases the blebbing of vesicles from them, supporting the hypothesis that entropic forces exerted by MUC1 change the spontaneous curvature of cell membranes. However, how MUC1 is incorporated into and influences the size and biophysical properties of plasma-membrane-blebbed vesicles is not understood. Here we report single-vesicle-level characterization of giant plasma membrane vesicles (GPMVs) derived from cells overexpressing MUC1, revealing a 40× variation in MUC1 density between GPMVs from a single preparation and a strong correlation between GPMV size and MUC1 density. By dispersing GPMVs in aqueous liquid crystals (LCs), we show that the elasticity of the LC can be used to strain individual GPMVs into spindle-like shapes, consistent with the straining of fluid-like membranes. To quantify the influence of MUC1 on membrane mechanical properties, we analyze the shapes of strained GPMVs within a theoretical framework that integrates the effects of MUC1 density and GPMV size on strain. We measure the spontaneous curvature of GPMV membranes to be 2-10 μm-1 and weakly influenced by the 40× variation in MUC1 density, a conclusion we validate by performing independent experiments in which MUC1 is enzymatically removed from GPMVs. Overall, our study advances the understanding of heterogeneity in size and MUC1 density in GPMVs, and establishes single-vesicle-level methods for characterization of mechanical properties within a heterogeneous population of GPMVs. Furthermore, our measurements highlight differences between membrane properties of GPMVs and their parent cells.

Inspect quantitative signals in placental histopathology: Computer-assisted multiple functional tissues identification through multi-model fusion and distillation framework.

Pathological analysis of placenta is currently a valuable tool for gaining insights into pregnancy outcomes. In placental histopathology, multiple functional tissues can be inspected as potential signals reflecting the transfer functionality between fetal and maternal circulations. However, the identification of multiple functional tissues is challenging due to (1) severe heterogeneity in texture, size and shape, (2) distribution across different scales and (3) the need for comprehensive assessment at the whole slide image (WSI) level. To solve aforementioned problems, we establish a brand new dataset and propose a computer-aided segmentation framework through multi-model fusion and distillation to identify multiple functional tissues in placental histopathologic images, including villi, capillaries, fibrin deposits and trophoblast aggregations. Specifically, we propose a two-stage Multi-model Fusion and Distillation (MMFD) framework. Considering the multi-scale distribution and heterogeneity of multiple functional tissues, we enhance the visual representation in the first stage by fusing feature from multiple models to boost the effectiveness of the network. However, the multi-model fusion stage contributes to extra parameters and a significant computational burden, which is impractical for recognizing gigapixels of WSIs within clinical practice. In the second stage, we propose straightforward plug-in feature distillation method that transfers knowledge from the large fused model to a compact student model. In self-collected placental dataset, our proposed MMFD framework demonstrates an improvement of 4.3% in mean Intersection over Union (mIoU) while achieving an approximate 50% increase in inference speed and utilizing only 10% of parameters and computational resources, compared to the parameter-efficient fine-tuned Segment Anything Model (SAM) baseline. Visualization of segmentation results across entire WSIs on unseen cases demonstrates the generalizability of our proposed MMFD framework. Besides, experimental results on a public dataset further prove the effectiveness of MMFD framework on other tasks. Our work can present a fundamental method to expedite quantitative analysis of placental histopathology.

An integrated microfluidic device for sorting of tumor organoids using image recognition.

Tumor organoids present a challenge in drug screening due to their considerable heterogeneity in morphology and size. To address this issue, we proposed a portable microfluidic device that employs image processing algorithms for specific target organoid recognition and microvalve-controlled deflection for sorting and collection. This morphology-activated organoid sorting system offers numerous advantages, such as automated classification, portability, low cost, label-free sample preparation, and gentle handling of organoids. We conducted classification experiments using polystyrene beads, F9 tumoroids and patient-derived tumor organoids, achieving organoid separation efficiency exceeding 88%, purity surpassing 91%, viability exceeding 97% and classification throughput of 800 per hour, thereby meeting the demands of clinical organoid medicine.

THE EFFECT OF BLOOD PARAMETERS ON EMERGENCY DEPARTMENT FOLLOW-UP TIME AND HOSPITALIZATION STATUS IN COPD

BACKGROUND AND AIM Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease of the airways and lungs. Neutrophils are the blood cells that respond most early to inflammation. In many studies, the Neutrophil/Lymphocyte ratio has been shown to be an important component of the inflammatory response. RDW is a routine component of the hemogram, which shows heterogeneity in erythrocyte size and is used as a laboratory value for anemia. Research has shown that high RDW can be used as an indicator of poor prognosis in COPD. We aimed to show the effect of NLR and RDW values on morbidity by examining the correlation with length of hospital stay in COPD patients. MATERIALS AND METHODS Complete blood count data and length of hospital stay of COPD patients who were admitted to the emergency department of our hospital with symptoms of COPD exacerbation in the last six months were investigated retrospectively. The relationship between RDW values in complete blood count and neutrophil/lymphocyte ratios (NLR) in the emergency department and inpatient admission rates was examined. RESULTS A total of 101 patients, 69.3% of whom were male, were diagnosed with COPD and admitted to the emergency department with acute respiratory failure were included in the study. As a result of the statistical study, there is a significant difference in RDW-SW and NLR values according to the length of stay in the emergency department. CONCLUSION In our study, we observed that patients with higher RDW and NLR values had longer hospital stays. This has shown that RDW and NLR measurements may be important in determining the morbidity of the disease.

Primary Progressive Aphasia in Italian and English: A Cross-Linguistic Cohort Study.

Current formulations of primary progressive aphasia (PPA) derive largely from English-speaking patients. We hypothesized that language-specific characteristics influence PPA phenotypes in 2 contrasting languages: Italian and English. We undertook a retrospective, cross-sectional, observational comparison of 2 patient cohorts representing all major PPA syndromes, in London and Florence. Neuropsychological scores in a range of linguistic and general cognitive domains were normalized to native speaker controls and dichotomized as impaired/unimpaired. Proportions were compared using χ2 tests and adjusted for symptom duration and severity of cognitive impairment using logistic regression. The cohorts comprised 106 (48.1% female) Italian speakers (14 nonfluent/agrammatic [nfvPPA], 20 semantic [svPPA], 41 logopenic variant [lvPPA], 31 mixed PPA [mPPA]) and 166 (45.2% female) English speakers (70 nfvPPA, 45 svPPA, 42 lvPPA, 9 mPPA). Comparing cohorts, the English cohort was younger (mean 62.7 [SD = 8.4] vs 65.9 [7.8] years; p = 0.003, Cohen d = 0.39), with longer symptom duration (4.6 [4.3] vs 3.1 [2.5] years; p = 0.048, d = 1.08), a higher proportion of nfvPPA cases (42% vs 13%, χ2 = 25.4, p < 0.001), and lower proportions of lvPPA (25% vs 38%, χ2 = 5.46, p = 0.019) and mPPA (5% vs 29%, χ2 = 29.3, p < 0.001). English-speaking nfvPPA patients had less frequent expressive agrammatism (46% vs 93%, p = 0.015, odds ratio [OR] 16.05, 95% CI 1.70-151.13) but more frequently impaired single-word comprehension (60% vs 8%, p = 0.013, OR 0.06, 95% CI 0.00-0.56). English svPPA patients had more frequent surface dyslexia (68% vs 30%, p = 0.046, OR 0.24, 95% CI 0.06-0.97) and dysgraphia (38% vs 10%, p = 0.021, OR 0.09, 95% CI 0.01-0.70) while English lvPPA patients had more frequently impaired single-word comprehension (89% vs 29%, p < 0.001, OR 0.05, 95% CI 0.01-0.28), word repetition (61% vs 26%, p = 0.020, OR 0.24, 95% CI 0.07-0.80), nonword repetition (78% vs 30%, p = 0.010, OR 0.18, 95% CI 0.05-0.06), nonverbal working memory (69% vs 36%, p = 0.005, OR 0.10, 95% CI 0.02-0.51), and visuomotor function (89% vs 25%, p < 0.001, OR 0.02, 95% CI 0.01-0.20). Language-specific characteristics influenced PPA phenotypes, with more frequent expressive agrammatism in Italian (reflecting its morphologic complexity), more frequently impaired word processing in English (reflecting its articulatory, acoustic, and orthographic complexity), and increased prevalence of mPPA in Italian. These findings have implications for PPA diagnosis and management. Limitations of test heterogeneity and cohort size should be addressed in future, prospective, multicenter initiatives using cross-linguistic tools.

Influence of network heterogeneity on the nanoscale mechanical properties of epoxy resins

AbstractThe presence of structural heterogeneities in glassy epoxy networks can strongly affect the adhesiveness and mechanical properties of epoxy-based materials. Recent studies have demonstrated that the size and architecture of structural heterogeneities can be monitored during the curing process, thus providing an effective way to control multiple physical properties of epoxy resins. However, because the size of heterogeneities is believed to be at the nanoscale, obtaining insights into the direct correlation between the local behavior of heterogeneities and the preparation conditions remains challenging. Here, we combine two recently developed atomic force microscopy (AFM)-based methods, bimodal amplitude and frequency modulation and nanoscale dynamic mechanical analysis (nDMA), to directly visualize and quantify the nanoscale mechanical properties of epoxy resins obtained via different curing conditions. Our AFM maps clearly show a correlation between the curing conditions and the heterogeneous behavior of the resulting epoxy networks, which is in excellent agreement with those predicted from macroscopic measurements. Notably, our nDMA results revealed a relationship between network heterogeneity and the glass transition behavior of the epoxy resins.

Cryoneurolysis for phantom limb pain: a systematic review.

Phantom limb pain (PLP) is a painful sensation occurring in patients around the site of an amputation. The aim of this systematic review is to evaluate the efficacy of cryoneurolysis in the management of phantom limb pain. A systematic review was performed according to the PRISMA 2020 guidelines. An initial search yielded 200 articles from four major scientific databases (PubMed, Embase, Cochrane Library, WebOfScience). Five articles met inclusion criteria, four of which underwent additional pooled statistical analysis. Pooled analysis of the included trials revealed a cumulative Cohen's d effect size of 1.55 (95% CI [0.24, 2.87]; p = 0.02; z = 2.32) for the reduction of pain on a 10-point pain scale following cryoneurolysis intervention. The remaining article that did not meet inclusion criteria for statistical analysis was a case report that reported a reduction in pain from 9/10 to 1/10 one week following intervention. The large effect size demonstrated a statistically and clinically significant improvement in patient-reported pain. Additionally, patients may be able to reduce their amount of pharmaceutical pain management with successful cryoneurolysis treatment. However, these findings are limited by the small sample size and high heterogeneity between studies. Further high-quality studies should be performed to corroborate these findings. www.crd.york.ac.uk/prospero identifier is CRD42024543085.

The Relationship Between Game-Related Assessment and Traditional Measures of Cognitive Ability-A Meta-Analysis.

Technological advances have introduced new methods for assessing psychological constructs, moving beyond traditional paper-pencil tests. Game-related assessments (GRAs) offer several advantages for research and practice, though questions about their construct validity persist. This meta-analysis investigated the relationship between indicators derived from computer-based games and traditional cognitive ability measures, examining whether measurement scope (single vs. multiple indicators) or measurement medium of cognitive ability (computer-based vs. paper-pencil) influences this relationship. We identified 52 eligible samples stemming from 44 papers, including data from over 6100 adult participants. The results from three-stage mixed-effects meta-analyses showed an overall observed correlation of r = 0.30 (p < 0.001; corrected r = 0.45) between GRA indicators and traditional cognitive ability measures with substantial heterogeneity in effect sizes. Stronger relationships were found when cognitive ability was measured by multiple indicators, but no differences emerged based on the measurement medium of cognitive ability. Furthermore, GRAs intended to assess cognitive ability did not show stronger relationships with traditional measures of cognitive ability than GRAs not specifically used to measure cognitive ability. Overall, our findings suggest that GRAs are related to traditional cognitive ability measures. However, the overall effect size raises questions about whether GRAs and traditional measures capture the same aspects of cognitive ability or if GRAs also measure other constructs beyond cognitive ability.

Treatments for Depression and Trauma-Related Symptoms for Adult Survivors of Sexual Violence: A Preliminary Meta-Analysis

This meta-analysis analyzed the effectiveness of interventions for adult sexual violence survivors for symptoms of trauma and depression. Twelve between-group studies (N = 741) were identified that met the inclusion criteria and were included in our analyses. Results showed that the treatment effects of interventions for sexual violence survivors are statistically significant, with large Hedge’s G effect sizes. However, there was significant heterogeneity in effect sizes for treatments compared to alternative treatments. Moderator analyses that examined the number of treatment sessions and treatment format did not significantly influence the treatment effect. Further research is needed to ascertain the impact of various interventions for treating sexual violence.

Otoprotective Effects of Sodium Thiosulfate by Demographic and Clinical Characteristics: A Report From Children's Oncology Group Study ACCL0431.

ACCL0431 was a randomized clinical trial that demonstrated efficacy of sodium thiosulfate (STS) for preventing cisplatin-induced hearing loss (CIHL) among patients 1-18years old. The purpose of this study was to evaluate possible differential STS otoprotection among patient subgroups. This secondary analysis included ACCL0431 participants treated with cisplatin and randomized to receive STS or not (observation). Hearing status was obtained at 4weeks and 12months post cisplatin therapy (SIOP Ototoxicity Scale). Cumulative incidence of CIHL (Grade 1+) was assessed across age, sex, race/ethnicity, cancer diagnosis, and cisplatin infusion duration. Associations between these variables and CIHL were assessed using multivariable logistic regression. Interaction terms were used to evaluate potential heterogeneity in STS effect sizes across subgroups. Among evaluable participants (n = 121), CIHL incidence was 22.4% with STS and 54.0% with observation. Odds of developing CIHL were greatest among children less than 5years versus older (randomization-adjusted odds ratio [OR] 2.94, 95% CI: 1.30-7.14) and those with neuroblastoma, hepatoblastoma, or medulloblastoma versus germ cell tumor or osteosarcoma (age- and randomization-adjusted OR 11.26, 95% CI: 3.08-47.35). STS otoprotective effect sizes were also greatest in the same highest risk groups by age (<5years: OR 0.08, 95% CI: 0.02-0.32; ≥5years: OR 0.39, 95% CI: 0.15-1.06) and cancer diagnosis (neuroblastoma/hepatoblastoma/medulloblastoma: OR 0.1, 95% CI: 0.02-0.45; germ cell tumor/osteosarcoma: OR 0.32, 95% CI: 0.06-1.25). Significant otoprotection from STS was noted across other subgroups with varied magnitudes of effect. STS otoprotection appears to differ across clinically meaningful subgroups, particularly age at diagnosis. These results inform clinical decision-making and future research.

Privacy-by-Design with Federated Learning will drive future Rare Disease Research

Up to 6% of the global population is estimated to be affected by one of about 10,000 distinct rare diseases (RDs). RDs are, to this day, often not understood, and thus, patients are heavily underserved. Most RD studies are chronically underfunded, and research faces inherent difficulties in analyzing scarce data. Furthermore, the creation and analysis of representative datasets are often constrained by stringent data protection regulations, such as the EU General Data Protection Regulation. This review examines the potential of federated learning (FL) as a privacy-by-design approach to training machine learning on distributed datasets while ensuring data privacy by maintaining the local patient data and only sharing model parameters, which is particularly beneficial in the context of sensitive data that cannot be collected in a centralized manner. FL enhances model accuracy by leveraging diverse datasets without compromising data privacy. This is particularly relevant in rare diseases, where heterogeneity and small sample sizes impede the development of robust models. FL further has the potential to enable the discovery of novel biomarkers, enhance patient stratification, and facilitate the development of personalized treatment plans. This review illustrates how FL can facilitate large-scale, cross-institutional collaboration, thereby enabling the development of more accurate and generalizable models for improved diagnosis and treatment of rare diseases. However, challenges such as non-independently distributed data and significant computational and bandwidth requirements still need to be addressed. Future research must focus on applying FL technology for rare disease datasets while exploring standardized protocols for cross-border collaborations that can ultimately pave the way for a new era of privacy-preserving and distributed data-driven rare disease research.

Improving Circulating Tumor Cell Detection Using Image Synthesis and Transformer Models in Cancer Diagnostics.

Cancer is the second leading cause of death, significantly threatening human health. Effective treatment options are often lacking in advanced stages, making early diagnosis crucial for reducing mortality rates. Circulating tumor cells (CTCs) are a promising biomarker for early detection; however, their automatic detection is challenging due to their heterogeneous size and shape, as well as their scarcity in blood. This study proposes a data generation method using the Segment Anything Model (SAM) combined with a copy-paste strategy. We develop a detection network based on the Swin Transformer, featuring a backbone network, scale adapter module, shape adapter module, and detection head, which enhances CTC localization and identification in images. To effectively utilize both generated and real data, we introduce an improved loss function that includes a regularization term to ensure consistency across different data distributions. Our model demonstrates exceptional performance across five evaluation metrics: accuracy (0.9960), recall (0.9961), precision (0.9804), specificity (0.9975), and mean average precision (mAP) of 0.9400 at an Intersection over Union (IoU) threshold of 0.5. These results are achieved on a dataset generated by mixing both public and local data, highlighting the robustness and generalizability of the proposed approach. This framework surpasses state-of-the-art models (ADCTC, DiffusionDet, CO-DETR, and DDQ), providing a vital tool for early cancer diagnosis, treatment planning, and prognostic assessment, ultimately enhancing human health and well-being.

Multi-Analytical Approach for the Acid-Base, Thermal and Surface Properties Assessment of Waste Biomasses.

A multi-analytical approach was used to comprehensively characterize the acid-base, thermal, and surface properties of agri-food processing wastes (i.e., original and pre-treated bergamot, grape and olive pomaces). These biomasses, often underutilised and inadequately studied in terms of their physicochemical properties, were investigated under varying ionic strength conditions at t = 25 °C. This investigation uniquely integrates multiple advanced techniques: Brunauer-Emmett-Teller porosimetry, Scanning Electron Microscopy, Thermogravimetric Analysis coupled with Fourier Transform Infrared Spectroscopy, Differential Scanning Calorimetry, Attenuated Total Reflectance Fourier-Transform Infrared, and potentiometry to provide a holistic understanding of these biomasses potential for environmental remediation. The modelling of ionic strength-dependent acid-base behaviour, established using an extended Debye-Hückel-type equation, revealed the dominant role of carboxylic groups as active sites across all pomace types, although with variations in abundances across the different samples. Additionally, morphological analysis highlighted the presence of irregularly shaped particles, heterogeneous size distributions, and distinct thermal stability trends, with grape pomace exhibiting the highest mass loss. These findings underscore the significant potential of these biomasses for the remediation of cationic pollutants from natural waters. Moreover, this comprehensive characterisation not only advances the understanding of agri-food waste valorisation but also provides a robust framework for designing targeted strategies in environmental applications.

Estimating effective reproduction numbers using wastewater data from multiple sewersheds for SARS-CoV-2 in California counties.

The effective reproduction number serves as a metric of population-wide, time-varying disease spread. During the early years of the COVID-19 pandemic, this metric was primarily derived from case data, which has varied in quality and representativeness due to changes in testing volume, test-seeking behavior, and resource constraints. Deriving nowcasting estimates from alternative data sources such as wastewater provides complementary information that could inform future public health responses. We estimated county-aggregated, sewershed-restricted wastewater-based SARS-CoV-2 effective reproduction numbers from May 1, 2022 to April 30, 2023 for five counties in California with heterogeneous population sizes, clinical testing rates, demographics, wastewater coverage, and sampling frequencies. We used two methods to produce sewershed-restricted effective reproduction numbers, both based on smoothed and deconvolved wastewater concentrations. We then population-weighted and aggregated these sewershed-level estimates to arrive at county-level effective reproduction numbers. Using mean absolute error (MAE), Spearman's rank correlation (ρ), confusion matrix classification, and cross-correlation analyses, we compared the timing and trajectory of our two wastewater-based models to: (1) a publicly available, county-level ensemble of case-based estimates, and (2) county-aggregated, sewershed-restricted case-based estimates. Both wastewater models demonstrated high concordance with the traditional case-based estimates, as indicated by low mean absolute errors (MAE ≤ 0.09), significant positive Spearman correlation (ρ ≥ 0.66), and high confusion matrix classification accuracy (≥ 0.81). The relative timings of wastewater- and case-based estimates were less clear, with cross-correlation analyses suggesting strong associations for a wide range of temporal lags that varied by county and wastewater model type. This methodology provides a generalizable, robust, and operationalizable framework for estimating county-level wastewater-based effective reproduction numbers. Our retrospective evaluation supports the potential usage of real-time wastewater-based nowcasting as a complementary epidemiological tool for surveillance by public health agencies at the state and local levels. Based on this research, we produced publicly available wastewater-based nowcasts for the California Communicable diseases Assessment Tool (calcat.cdph.ca.gov).

High-speed rail and urban energy efficiency: Evidence from China

It is essential to explore the effect of high-speed rail on energy efficiency to develop medium and long-term green development plans and realize the “dual-carbon target” in China. We utilize urban nighttime light brightness data to measure the energy efficiency of 281 cities in China from 2006 to 2021. We investigate the relationship between the high-speed rail opening and the energy efficiency of cities using the difference-in-differences model. Further, we examine the temporal dynamics of urban energy efficiency improvement by the opening of high-speed rail. We find that the high-speed rail opening significantly improves urban energy efficiency, in which the long-term effect is more influential than the short-term. In addition, we explore the heterogeneity of geographic location, city level, and city size. The results suggest that the high-speed rail opening has a more significant effect on energy efficiency in the eastern region, first-tier cities, and large cities, providing evidence of the “siphon effect” of HSR. Four robustness tests confirm the reliability of the research: replacing core explanatory variables, PSM-DID, counterfactual test, and instrumental variable method.

Assessing advances in three decades of clinical antiretroviral therapy on the HIV-1 reservoir.

Antiretroviral therapy (ART) has improved the clinical management of HIV-1 infection. However, little is known about how the latest ART recommendations affect the heterogeneity of HIV-1 reservoir size. We used a complete statistical approach to outline parameters underlying diversity in HIV-1 reservoir size in a cohort of 892 people with HIV-1 (PWH) on suppressive ART for >3 years. Total HIV-1-DNA levels were measured in PBMCs using digital droplet PCR (ddPCR). We classified 179 (20%) participants as Low Viral Reservoir Treated (LoViReT, <50 HIV-1-DNA copies/106 PBMCs). Twenty variables were collected to explore their association with the LoViReT phenotype using machine learning approaches. Nadir CD4 and zenith pre-ART viral load were closely associated with LoViReT status, with lower CD4 recovery, shorter time from diagnosis to undetectable viral load, and initiation of treatment with an integrase inhibitor (InSTI)-containing regimen. Initiating ART with any InSTI was also associated with shorter time to undetectable viremia. Locally estimated scatterplot smoothing (LOESS) regression revealed a progressive reduction in the size of the HIV-1 reservoir in individuals who started ART after 2007. Similarly, higher nadir CD4 and shorter time to undetectable viremia were observed when treatment was initiated after that year. Our findings demonstrate that the progressive implementation of earlier, universal treatment at diagnosis and the use of InSTIs affect the size of the HIV-1 reservoir. Our work shows that effective management of infection is the first step toward reducing the reservoir and brings us closer to achieving a cure. U.S. National Institutes of Health, Division of AIDS at the National Institute of Allergy and Infectious Diseases, Merck Sharp & Dohme.

Source-rock and petrophysical evaluation of the Late Cretaceous Haymana Formation, Haymana Basin, Central Anatolia, Turkey

This study investigates the petroleum potential of mudstones of the Late Cretaceous Haymana Formation in the Haymana Basin, Turkey. The lithofacies, pore structure and source-rock characteristics of the mudstones are examined using stratigraphic, sedimentological, petrophysical and organic geochemical methods along four stratigraphic sections and other sampling sites. The depositional model presents a facies distribution within a submarine fan system. According to the bulk mineralogy, the identified lithofacies are mixed mudstone, mixed siliceous mudstone, marl, mixed carbonate mudstone, argillaceous/siliceous mudstone and clay-rich siliceous mudstone. XRD and mercury intrusion measurements suggest that the macropores (&gt;50 nm) of the mudstones formed by dissolution of calcite, while mesopores (2–50 nm) developed around the clay–quartz/feldspar. Of the analysed samples, no lithofacies class is distinct with any specific range of porosity or permeability, which suggests a strong heterogeneity in pore throat size, mineral content and grain size. The black shale from the NW of the basin with a total organic carbon (TOC) content of 1.19%, S1 value of 0.07 mg g −1 , S2 value of 1.01 mg g −1 and a T max value of 441°C is a relatively more mature source rock, although it still exhibits a poor petroleum potential. Overall, the TOC values (average of 0.38%) of the mudstones suggest organic-poor rock characteristics for the Haymana Formation in the studied parts of the Haymana Basin.