Counting Measurements Research Articles

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructure and connectivity. Yet, quantitative analysis of DW-MRI data is hindered by inconsistencies stemming from varying acquisition protocols. Specifically, there is a pressing need to harmonize the preprocessing of DW-MRI datasets to ensure the derivation of robust quantitative diffusion metrics across acquisitions. In the MICCAI-CDMRI 2023 QuantConn challenge, participants were provided raw data from the same individuals collected on the same scanner but with two different acquisitions and tasked with preprocessing the DW-MRI to minimize acquisition differences while retaining biological variation. Harmonized submissions are evaluated on the reproducibility and comparability of cross-acquisition bundlewise microstructure measures, bundle shape features, and connectomics. The key innovations of the QuantConn challenge are that (1) we assess bundles and tractography in the context of harmonization for the first time, (2) we assess connectomics in the context of harmonization for the first time, and (3) we have 10x additional subjects over prior harmonization challenge, MUSHAC and 100x over SuperMUDI. We find that bundle surface area, fractional anisotropy, connectome assortativity, betweenness centrality, edge count, modularity, nodal strength, and participation coefficient measures are most biased by acquisition and that machine learning voxel-wise correction, RISH mapping, and NeSH methods effectively reduce these biases. In addition, microstructure measures AD, MD, RD, bundle length, connectome density, efficiency, and path length are least biased by these acquisition differences. A machine learning approach that learned voxelwise cross-acquisition relationships was the most effective at harmonizing connectomic, microstructure, and macrostructure features, but requires the same subject be scanned at each site co-registered. NeSH, a spatial and angular resampling method, was also effective and has generalizable framework not reliant co-registration. Our code is available at <a href='https://github.com/nancynewlin-masi/QuantConn/'>https://github.com/nancynewlin-masi/QuantConn/</a>

Correlation of Hemoglobin, Albumin, Lymphocyte, and Platelets (HALP) Score With Outcome of Acute Ischemic Stroke.

Acute ischemic stroke (AIS) stands as a primary cause of both mortality and enduring disability. Given its significant impact on public health, efforts are ongoing to improve prognostic instruments and treatment approaches for this illness. In recent years, attention has been drawn towards the exploration of novel indicators of hemoglobin, albumin, lymphocyte, and platelets (HALP) that measure systemic inflammation and nutritional status. This study aims to investigate the relationship between the HALP score and the outcome of an acute ischemic stroke. This prospective observational study was conducted at a tertiary care hospital, with approval from the Institutional Ethical Committee. A total of 100 AIS patients were enrolled in the study, and their demographic details were collected. Within 24 hours of stroke onset, laboratory tests were performed, including measurements of albumin, hemoglobin, lymphocytes, and platelet count. The HALP scores of these patients were recorded. The severity of AIS was assessed using the National Institutes of Health Stroke Scale (NIHSS) upon admission. This study comprised 100 patients, with 66% and 44% being male and female, respectively, with a standard deviation of age 63. Following 28 days of in-hospital care and a 90-day outpatient follow-up, 16 patients were categorized as the non-survival group. The results showed a significant difference in hemoglobin values in the admitted groups (p = 0.04). Lymphocyte counts were higher in survivors compared to non-survivors with non-significant (p = 0.105). Furthermore, the HALP score of survivors is (a median of 34.0) and for non-survivors is (a median of 24.0), which showed a significant difference with a p-value of 0.022 and is statistically significant. Conclusion: Lower HALP score is associated with increased mortality in stroke patients. The HALP score emerges as a potentially valuable predictor of mortality in critically ill patients. This underscores the importance of considering the HALP score in prognostic assessments and treatment decisions for individuals affected by stroke.

Improving cellular therapy operations through pre-harvest measurement of peripheral CD34-positive cell counts in allogeneic stem cell harvest.

Previously, our institution measured peripheral blood CD34 cell counts both pre- and post-peripheral blood stem cell harvest (PBSCH), with both samples analyzed simultaneously post-PBSCH. Since 2021, we have measured pre-CD34 cell counts during PBSCH, adjusting the processed blood volume based on these results. We retrospectively evaluated how this change impacted cellular therapy. Related healthy donors were included and divided into 1-day and 2-day harvest cohorts. Donors with CD34 cell counts measured post- and during PBSCH were categorized into the previous and current sub-cohorts, respectively. Regarding the 1-day cohort (n = 212), the current sub-cohort had a significantly shorter average harvest duration (151 [standard deviation, SD = 45.1] vs. 180 [SD = 27.8] minutes, respectively) and higher average infusion rates (87.6% [SD = 21.1] vs. 78.1% [SD = 25.7], respectively) than the previous sub-cohort. Adjusting the processed blood volume based on pre-PBSCH CD34 cell counts measured during the harvest may reduce donor burden and enhance workflow efficiency.

Generation of a tripartite photonic state via a double-Λ configuration in a four-level system

Triphotons have a more abundant energy structure compared to biphotons. Furthermore, as the number of photons increases, excellent properties such as entangled multi-qubit states, high security, flexibility, and information capacity are observed. This leads to a growing demand for multi-body quantum information processing. Here, a method is proposed to generate a three-photon entangled state using a single six-wave mixing process in an atomic ensemble. The research examines the temporal correlation characteristics of the triphoton produced in photon coincidence counting measurements, with a focus on the linear and nonlinear susceptibilities of the six-wave mixing process. These properties primarily depend on the fifth-order nonlinear coupling coefficients responsible for the damping Rabi oscillations and the group delay determined by the longitudinal detuning function. To enhance the nonlinear interaction between the optical field and the atomic ensemble, placing the atomic ensemble in a high-quality cavity and utilizing laser cooling techniques to eliminate the internal Doppler broadening effect in the atomic gas hold promise.

Soil-transmitted helminth (STH) infections in the Wolaita zone in Southern Ethiopia: mid-stage evaluation of the Geshiyaro project and progress towards the interruption of transmission

BackgroundThis paper documents changes in the prevalence and intensity of soil-transmitted helminth (STH) infections in the Geshiyaro project in the Wolaita zone of Southern Ethiopia.MethodsThe Geshiyaro project comprises three intervention arms. Arm 1 is subdivided into the Arm 1 pilot (one district) and Arm 1 (four other districts), both receiving integrated community-wide mass drug administration MDA (cMDA) with intensive water, sanitation, and hygiene (WaSH) interventions. Arm 2 involves 18 districts with cMDA interventions plus the existing government-led One WaSH program, while Arm 3 serves as a control with school-based MDA (sMDA) interventions plus the existing government-led One WaSH program in three districts. The study is designed as a cohort investigation over time, with the establishment of longitudinal sentinel sites where infection levels are assessed annually. A total of 45 longitudinal parasitological surveillance sentinel sites are being used across all three intervention arms to monitor STH prevalence and intensity of infection. From each of the 45 sentinel sites, 150 individuals were randomly selected, stratified by age and gender. The t-test and analysis of variance (ANOVA) were employed to compare infection prevalence and intensity across the three study arms over time.ResultsThe prevalence of STH decreased significantly from 34.5% (30.6%, 38.5%) in 2019 to 10.6% (8.3%, 13.4%) in 2022/2023 (df = 1, P < 0.0001) in the Arm 1 pilot, from 27.4% (25.2%, 29.7%) in 2020 to 5.5% (4.4%, 6.7%) in 2023 (df = 1, P < 0.0001) in Arm 1, from 23% (21.3%, 24.8%) in 2020 to 4.5% (3.7%, 5.3%) in 2023 (df = 1, P < 0.001) in Arm 2, and from 49.6% (47.4%, 51.7%) in 2021 to 26.1% in 2023 (df = 1, P < 0.0001) in Arm 3. The relative reduction in the prevalence of any STH was the highest in the arms employing cMDA, namely Arm 2, with a decrease of 82.5% (79.3%, 84.2%), followed by Arm 1 with a reduction of 80.1% (75.3%, 84.6%), and then the Arm 1 pilot with a decrease of 69.4% (60.1%. 76.6%). Arm 3 employing sMDA had the lowest decrease, with a reduction of 46.9% (43.6%, 51%). The mean intensity of infection (based on Kato–Katz egg count measures) for Ascaris lumbricoides species, which was the dominant STH species present in the study area, decreased significantly in Arms 1 and 2, but only slightly in Arm 3. The prevalence of hookworm and Trichuris trichiura infections were found to be very low in all arms but also decreased significantly.ConclusionsThe reduction in the prevalence and intensity of STH in Arms 1 and 2 revealed steady progress towards transmission interruption based on cMDA intervention, but additional efforts with MDA coverage and WaSH interventions are needed to achieve a prevalence threshold < 2% based on the quantitative polymerase chain reaction (qPCR) diagnostic method.Graphical

Risk factors for prolonged length of hospital stay following elective hip replacement surgery: a retrospective longitudinal observational study

ObjectivesOur aim was to identify which patients are likely to stay in hospital longer following total hip replacement surgery.DesignLongitudinal, observational study used routinely collected data.SettingData were collected from an NHS...

Phytomass carbon pools of Koivulambisuo mire system (South Karelia)

Koivulambisuo mire system (61,80º N, 33,56º E, middle taiga subzone) has a complex structure of vegetation cover, includes south karelian variant of aapa mires, raised bogs, transitional herb-sphagnum fens and forested sites of different trophic levels.The study was carried out within the framework of the National system for monitoring carbon pools and greenhouse gas fluxes in Russia. Phytomass and carbon pools were determined for three types of mire sites: aapa, ridge-hollow sphagnum bog and oligotrophic pine-dwarf shrub-cotton grass-sphagnum. On each type of mire sites, 3 sample plots 50x50 m in size were set up, with 8–12 sampling points on each. Tree stand estimated by total count and basic measurements of all standing trees on plots, production of needles and branches by model tree method. The above-ground vascular plants phytomass material was collected by the cutting method, mosses and underground phytomass by monoliths method, the production of sphagnum mosses by annual increment method. Aapa mire extremely poorly afforested, to the least extent among the studied sites, due to strong watering and poor development of strings. The total carbon pool in a forest stand is only 0.01 tC/ha. The carbon pool in the above-ground phytomass of aapa complexes is also minimal – 2.56 tC/ha. It is mainly provided by sphagnum mosses, while herbs and shrubs contain half as much carbon in total. Living underground phytomass deposits 21.56 tC/ha (89% of the total phytomass). Such a high carbon sequestration by living underground plant organs is a feature of aapa sites and is associated with favorable regime of water movement. Some overestimation is also possible due to the difficulty of separating living and dead tightly intertwined roots. The mortmass of a 40 cm surface layer of peat soil contains 38.71 tC/ha, most of it in the sphagnum remains. The annual ground cover production of aapa is minimal: 1.55 tC/ha, which is caused by the development of extensive flarks with sparse vegetation cover. Unlike other sites, the role of vascular plants is higher here (0.68 tC/ha) due to the predominance of herbaceous plants in cover. The afforestation degree of ridge-hollow bogs varies; the living forest stand of the most afforested sites is contains 0.31 tC/ha, while in the other two, more watered sites, the pool is less than 0.02 tC/ha. The average carbon stock in a tree stand is 0.11 tC/ha. The carbon pool in the ground cover of the ridge-hollow bogs is maximum among the studied mire sites (4.25 tC/ha), the main share in it is sphagnum mosses (3.52 tC/ha), while grasses and shrubs 0.73 tC/ha. Living underground phytomass deposits 8.62 tC/ha (66% of the total phytomass).The mortmass of a 40 cm surface layer of peat soil contains, on average, 61.77 tC/ha, most of it in the sphagnum remains. In cotton grass-sphagnum hollows the stock reaches 80.09 tC/ha due to dense cotton grass tussocks. The above-ground vascular plants annual production is 0.48 tC/ha (the minimum among the studied mire site types) and 1.56 tC/ha by mosses. Pine-dwarf shrub-cotton grass-sphagnum plots have the most developed forest stands among the studied mire sites. The average tree height here is 1-2 m, individual trees reach a 5-6 m. The carbon pool in the living tree stand is 2.92 tC/ha, in dead wood – 1.66 tC/ha. Accordingly, the forest stand contribution to the total living phytomass carbon stock is maximum here and equal to moss stock. In the ground cover is deposited 4.46 tC/ha, besides sphagnum mosses (2.9 tC/ha), a significant stock in dwarf shrubs (1.11 tC/ha). Living underground phytomass deposits 9.04 tC/ha (56% of the total phytomass). The mortmass of a 40 cm surface layer of peat soil contains 63.43 tC/ha. The total contribution of pine needles and branches to the annual production is 0.04 tC/ha. The above-ground phytomass here also demonstrates the maximum annual production – 2.21 tC/ha per year, mainly provided by sphagnum mosses (1.64 tC/ha). In general, the main living phytomass carbon pools of mire sites are concentrated in the underground parts of vascular plants. The ground cover main stock is in sphagnum mosses. Significant carbon stock in the tree stands only has pine-cotton grass-dwarf shrub-sphagnum sites, where it equal to the carbon stock of mosses. In all types of sites, carbon pool in the mortmass of the upper 40 cm of the deposit are noticeably higher than the total reserves in living phytomass. The main part of the mortmass consists of the sphagnum mosses remains. Mosses are also characterized by the largest primary annual production of carbon.

Associations of CD4 Cell Count Measures With Infection-Related and Infection-Unrelated Cancer Risk Among People With HIV.

People with HIV are at higher risk of infection-related cancers than the general population, which could be due, in part, to immune dysfunction. Our objective was to examine associations between 4 CD4 count measures as indicators of immune function and infection-related and infection-unrelated cancer risk. We conducted a cohort study of adults with HIV who were diagnosed with cancer in Ontario, Canada. Incident cancers were identified from January 1, 1997 to December 31, 2020. We estimated adjusted hazard ratios (aHR) for the associations between CD4 measures (baseline CD4, nadir CD4, time-updated CD4, time-updated CD4:CD8) and cancer incidence rates using competing risk analyses, adjusted for socio-demographic factors, history of hepatitis B or C infection, baseline viral load, smoking, and alcohol use. Among 4771 people with HIV, contributing 59,111 person-years of observation, a total of 549 cancers were observed. Low baseline CD4 (<200 cells/µL) (aHR 2.08 [95% CI: 1.38 to 3.13], nadir (<200 cells/µL) (aHR 2.01 [95% CI: 1.49 to 2.71]), low time-updated CD4 (aHR 3.52 [95% CI: 2.36 to 5.24]) and time-updated CD4:CD8 ratio (<0.4) (aHR 2.02 [95% CI: 1.08 to 3.79]) were associated with an increased rate of infection-related cancer. No associations were observed for infection-unrelated cancers. Low CD4 counts and indices were associated with increased rates of infection-related cancers among people with HIV, irrespective of the CD4 measure used. Early diagnosis and linkage to care and high antiretroviral therapy uptake may lead to improved immune function and could add to cancer prevention strategies such as screening and vaccine uptake.

Timing of SMN replacement therapies in mouse models of spinal muscular atrophy: a systematic review and meta-analysis.

Mutations in the Survival of Motor Neuron 1 gene lead to a loss of survival motor neuron protein in patients with spinal muscular atrophy. Revolutionary advances in gene therapy have led to survival motor neuron-replacement therapies that significantly prolong life expectancy and improve neuromuscular function. However, accumulating evidence suggests that the timing of survival motor neuron-replacement therapies is a critical determinant of success. We performed a systematic review and meta-analysis of all pre-clinical studies testing survival motor neuron replacement therapies in mouse models of spinal muscular atrophy to assess the impact of timing of delivery on therapeutic effectiveness. We incorporated four databases in this pre-registered study (PROSPERO 2020 CRD42020200180): EMBASE, PubMed, Scopus and Web of Science. Inclusion criteria were; primary research article, a measure of survival analysis, use of survival motor neuron mouse model and evaluation of survival motor neuron-targeting therapy. Exclusion criteria included; use of therapies not known to directly target survival motor neuron, genetic manipulations and/or lack of appropriate controls. We screened papers using the SyRF platform. The main outcome we assessed was survival in treated groups compared to untreated groups. We performed meta-analysis of survival using median survival ratio and the random effects model and measured heterogeneity using the I 2 statistic. Subgroup analyses were performed to assess treatment efficacy based on timing of intervention (embryonic delivery, day of birth, postnatal day 2 and postnatal day 3 or later) and treatment type. If detailed in the studies, body weight compared to untreated spinal muscular atrophy models and motor neuron number were included as secondary outcomes for meta-analysis. 3469 studies were initially identified, with 78 ultimately included. Survival motor neuron-replacement therapies significantly affected survival in favour of treatment by a factor of 1.20 (95% CI 1.10-1.30, P < 0.001) with high heterogeneity (I 2 = 95%). Timing of treatment was a significant source of heterogeneity (P < 0.01), with earlier treatment having a greater impact on survival. When stratified by type of treatment, earlier treatment continued to have the strongest effect with viral vector replacement therapy and antisense oligonucleotide therapy. Secondary outcome measures of body weight and spinal motor neuron counts were also positively associated with early treatment. Earlier delivery of survival motor neuron replacement therapies is therefore a key determinant of treatment efficacy in spinal muscular atrophy.

Dependence of photophysical properties on stereoisomers: The case of nonsymmetric 2-aryl(benz)imidazole-annulated derivatives

Nonsymmetric 2-aryl (benz)imidazole derivatives were previously synthesized via C-H/N-H annulation of imidazole derivatives from lapachol moieties with internal alkynes as an efficient tool to increase the π-system of lapimidazole derivatives. To investigate their photophysical properties, time-resolved and steady-state fluorescence measurements were carried out on dropcast film, powder, and diluted solution. Despite having the same number of single and double bonds, slight differences in their structures lead to distinct photophysical properties. The time-correlated single-photon counting measurements also demonstrated that the aspects of the temporal decay curves are dependent on the treatment of the samples during the measurements. The decay curves were relatively well fitted using an alternative method based on the exponentially modified Gaussian function, giving rise to a more complete set of fitting parameters. Finally, theoretical calculations corroborate that small structural changes in molecules can significantly alter their conformational dynamics, electronic spectra, and overall electronic behavior and stability.

White blood cell counts, ratios, and C-reactive protein among individuals with schizophrenia spectrum disorder and associations with long-term outcomes: a population-based study

BackgroundImmune mechanisms are associated with adverse outcomes in schizophrenia; however, the predictive value of various peripheral immune biomarkers has not been collectively investigated in a large cohort before. ObjectiveTo investigate how white blood cell (WBC) counts, ratios, and C-Reactive Protein (CRP) levels influence the long-term outcomes of individuals with schizophrenia spectrum disorder (SSD). MethodsWe identified all adults in the Central Denmark Region during 1994–2013 with a measurement of WBC counts and/or CRP at first diagnosis of SSD. WBC ratios were calculated, and both WBC counts and ratios were quartile-categorized (Q4 upper quartile). We followed these individuals from first diagnosis until outcome of interest (death, treatment resistance and psychiatric readmissions), emigration or December 31, 2016, using Cox regression analysis to estimate adjusted hazard ratios (aHRs). ResultsAmong 6,845 participants, 375 (5.5 %) died, 477 (6.9 %) exhibited treatment resistance, and 1470 (21.5 %) were readmitted during follow-up. Elevated baseline levels of leukocytes, neutrophils, monocytes, LLR, NLR, MLR, and CRP increased the risk of death, whereas higher levels of lymphocytes, platelets, and PLR were associated with lower risk. ROC analysis identified CRP as the strongest predictor for mortality (AUC=0.84). Moreover, elevated levels of leukocytes, neutrophils, monocytes, LLR, NLR and MLR were associated with treatment resistance. Lastly, higher platelet counts decreased the risk of psychiatric readmissions, while elevated LLR increased this risk. ConclusionsElevated levels of WBC counts, ratios, and CRP at the initial diagnosis of SSD are associated with mortality, with CRP demonstrating the highest predictive value. Additionally, certain WBC counts and ratios are associated with treatment resistance and psychiatric readmissions.

Correlation Among Neighborhood-level Measures of the Tobacco Retail Environment.

Tobacco retailer density and distance to tobacco retailers are understood to influence tobacco-related behaviors; however, there is no general agreement on how to best characterize or measure the tobacco retail environment (TRE). In this data-driven analysis, we examine similarities among neighborhood-level measures of the TRE and assess how geographic resolution of the neighborhood units may affect them. We used locations of likely tobacco retailers in the United States (US) to calculate multiple retailer count, density, and distance measures. Measures were calculated at the Census block group, tract, and county (including county equivalents) levels of geographic aggregation. Spearman's correlation was used to evaluate similarity among the TRE measures. At the block group and tract level, correlation among all TRE measures ranged from slightly negative (ρ = -0.03) to nearly perfect (ρ = 0.99). At both levels of aggregation, distance-based TRE measures were highly correlated (ρ > 0.76). At the block group level, simple count of retailers was highly correlated with the density measures (ρ > 0.83), and at the tract level, simple count was moderately to highly correlated with the density measures (ρ > 0.5). Findings were generally similar at the county level; a notable deviation was that retailers per person was negatively correlated with all other TRE measures (range from ρ = -0.08 to ρ = -0.32). Some common measures were not correlated, suggesting they capture different aspects of the TRE; similarity among the various measures also varied by level of geographic aggregation. Because the tobacco retail environment shapes people's tobacco-related behaviors, using appropriate measures to characterize it at a neighborhood-level is paramount. Our work highlights both the similarities and differences among a set of common measures, thereby suggesting the measures may be capturing different aspects of the overall retail environment. Our findings regarding geographic level of aggregation underscore the importance of neighborhood definition in any tobacco retail environment analysis.

Splenic Stiffness Measurement Combined With Liver Stiffness Measurement Compared With Baveno VII Criteria in Predicting the Presence of Oesophageal and Gastric Varices in Patients With Compensated Advanced Liver Cell Disease (cALCD).

Liver stiffness measurement (LSM) using vibration-controlled transient elastography (VCTE) is being increasingly used as a screening tool to predict varices. Our aim was to test the utility of Baveno VII criteria and other combinations of LSM, platelet count (PC), and splenic stiffness measurement (SSM) to predict the presence of varices in a cohort of Sri Lankan patients with compensated advanced liver cell disease (cALCD). Consecutive patients with newly diagnosed Child-Pugh class A cALCD (non-viral, BMI<30) were recruited prospectively. They underwent gastroscopy. LSM and SSM were taken using vibration-controlled transient elastography (VCTE) (Echosens FibroScan 502 Touch; Echosens SA, Paris, France) by a single operator who was unaware of endoscopy findings. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of different Baveno VII criteria to predict the varices and different combinations of LSM, SSM, and PC were also explored. One hundred and seventy-four individuals were recruited. The mean age was 61.4 ((95% CI: 59.7-62.8) years. A total of 110 individuals were males, and 106 had varices. Our results indicated that the three Baveno VII criteria had sensitivities of 61%, 63%, and 42%, and specificities of 79%, 77%, and 87% to predict varices. SSM>30kPa alone and in combination with LSM>15kPa had sensitivities of 81 and 75%, specificities of 72 and 83%, PPVs of 82 and 87%, NPVs of 71% and 67%, and accuracies of 78 and 78%, respectively, to predict varices. Baveno VII criteria had a low sensitivity but high specificity in predicting the presence of varices. However, SSM>30kPa alone or in combination with LSM>15kPa had better sensitivity, specificity, PPV, NPV, and accuracy in predicting varices.

The 100 Most-cited Articles in Autologous Breast Reconstruction: A Bibliometric Analysis.

Autologous breast reconstruction has continued to increase in popularity and witnessed significant advancements in aesthetic outcomes, patient satisfaction, and improved quality of life. We performed the first bibliometric analysis focused only on the 100 most-cited autologous breast reconstruction articles to characterize any emerging trends and assess the methodological quality of these studies. The 100 most-cited articles in autologous breast reconstruction were identified on Web of Science, across all available journals and years. Study details, including the citation count, main subject, and outcome measures, were extracted from each article, and the level of evidence was also assessed. The 100 most-cited articles in autologous breast reconstruction were cited by a total of 21,194 articles. Citation per article ranged significantly from 112 to 1123 (mean, 211.9). Overall, most of the top-cited articles are case reports/series (n = 32, mean citations = 243.2) and cohort studies (n = 30, mean citations = 211.2). This is closely followed by case-control studies (n = 29, mean citations = 183.6). Only four studies achieved level 1 status, underscoring a lack of high-quality methodological research in the field. Most studies (n = 72) highlighted autologous breast reconstruction outcomes, whereas 12 focused on its indications. There were nine studies exploring surgical techniques, and seven studies addressing the autologous breast reconstruction surgical anatomy. Overall, most of the influential articles in autologous breast reconstruction literature are of lower-level evidence. Contemporary research should focus on enhancing the study designs and measure clinical and patient-reported outcomes with validated tools, such as BREAST-Q.

Exploring cardiovascular health in children: the influence of Hemoglobin-to-Platelet ratio in contrasting rural and urban communities

ABSTRACT Understanding the associations and possible mechanisms between Cardiorespiratory Fitness (CRF) and residential location is an important focus of public health research. This is a cross-sectional study carried out with 2250 students (6–17 years), from southern Brazil. In addition to age, sex, and body size measurements, we also recorded hemoglobin and platelet count measurements using venous blood samples (10 ml). The CRF was measured using the 6-minute run/walk test, with predictors explored via allometry. Results identified a novel and independent association between the hemoglobin-to-platelet count ratio and children’s CRF, after controlling for confounders. We also provide evidence of a possible mechanism for this association, having identified reduced measures of hemoglobin and increased platelet counts observed in children living in urban (vs rural) areas. These results suggest the need for more effective public health practices and policies addressing the built enviroment´s health effects in Brazil and potentially other congested ciries.

Thermal Image Based Occupant Count Measurement Model using Human Body Temperature for Smart Building

Objectives: The proposed Occupant Count Measurement (OCM) model aims to enhance sustainability, energy efficiency, comfort, and safety in smart buildings by accurately determining occupant count using thermal camera images and body temperature data. Methods: The model leverages real-time thermal camera images without the need for a pre-existing dataset. Key parameters include temperature threshold, occupant motion, size, and shape to ensure accurate occupancy estimation. The K-means algorithm identifies and clusters regions of interest (ROI) in thermal images corresponding to human body temperatures. The model also employs sensors like PIR, RGB cameras, and thermal image sensors. Manual counting serves as a benchmark for comparison. Findings: The K-means algorithm extracts regions with elevated temperatures related to human bodies from thermal images, partitioning them into K-clusters based on temperature ranges and assigning each pixel to one of the clusters. A temperature threshold differentiates human clusters in the thermal image, while connected component labeling refines human object segmentation by identifying blobs, which are then used for occupant counting. The model's precision is assessed using diverse image sensors and compared to the actual number of occupants. The proposed OCM model achieves an accuracy of about 90.2% compared to traditional methods. Novelty: This study introduces an OCM model that uses thermal images to estimate the number of occupants in a room based on their body temperature. The method focuses on detecting and counting occupants by their overall thermal body signature, providing a novel approach to occupant measurement in smart buildings. Keywords: Thermal Images, Segmentation, Occupant Estimation, Occupant Comfort, Smart Building

AutoRefl: active learning in neutron reflectometry for fast data acquisition

Neutron reflectometry (NR) is a powerful technique for interrogating the structure of thin films at interfaces. Because NR measurements are slow and instrument availability is limited, measurement efficiency is paramount. One approach to improving measurement efficiency is active learning (AL), in which the next measurement configurations are selected on the basis of information gained from the partial data collected so far. AutoRefl, a model-based AL algorithm for neutron reflectometry measurements, is presented in this manuscript. AutoRefl uses the existing measurements of a function to choose both the position and the duration of the next measurement. AutoRefl maximizes the information acquisition rate in specific model parameters of interest and uses the well defined signal-to-noise ratio in counting measurements to choose appropriate measurement times. Since continuous measurement is desirable for practical implementation, AutoRefl features forecasting, in which the optimal positions of multiple future measurements are predicted from existing measurements. The performance of AutoRefl is compared with that of well established best practice measurements for supported lipid bilayer samples using realistic digital twins of monochromatic and polychromatic reflectometers. AutoRefl is shown to improve NR measurement speeds in all cases significantly.

A Deep-Learning-Based CPR Action Standardization Method.

In emergency situations, ensuring standardized cardiopulmonary resuscitation (CPR) actions is crucial. However, current automated external defibrillators (AEDs) lack methods to determine whether CPR actions are performed correctly, leading to inconsistent CPR quality. To address this issue, we introduce a novel method called deep-learning-based CPR action standardization (DLCAS). This method involves three parts. First, it detects correct posture using OpenPose to recognize skeletal points. Second, it identifies a marker wristband with our CPR-Detection algorithm and measures compression depth, count, and frequency using a depth algorithm. Finally, we optimize the algorithm for edge devices to enhance real-time processing speed. Extensive experiments on our custom dataset have shown that the CPR-Detection algorithm achieves a mAP0.5 of 97.04%, while reducing parameters to 0.20 M and FLOPs to 132.15 K. In a complete CPR operation procedure, the depth measurement solution achieves an accuracy of 90% with a margin of error less than 1 cm, while the count and frequency measurements achieve 98% accuracy with a margin of error less than two counts. Our method meets the real-time requirements in medical scenarios, and the processing speed on edge devices has increased from 8 fps to 25 fps.

The Influence of Varying Wavelengths of LED Light on the Development, Physiology Response, and Metabolism Activities of Micropropagated Dendrobium Hybrid ‘Shuijing’ Plantlets

Dendrobium hybrids have a significant role in the present floral sector. The aim of this research was to evaluate how various light qualities affect the physiological and biochemical traits of Dendrobium ‘Shuijing’. In order to determine the optimal light quality for in vitro cultivation of Dendrobium plantlets, we examined the correlations between growth, antioxidant capacity, and nutrient and chlorophyll levels, as well as chlorophyll fluorescence. The growth rate was compared by using different light qualities emitted by the LED light source. These included red light (R), blue light (B), and three ratios: 8R:2B, 7R:3B, and equal proportions of both colors, known as white, fluorescent light (CK). The combination of 7R:3B resulted in noticeable enhancements in leaf count, root length, root activity, fresh and dry weight measurements, antioxidant capability, as well as chlorophyll content and fluorescence. Specifically, the mixture of red and blue LED lights at a ratio of 7R:3B led to increased leaf number, root length, root activity, fresh and dry weight measurements, antioxidant ability, and chlorophyll content with improved fluorescence. In order to explore the effect of light quality on the growth and development of Dendrobium, the chlorophyll content and chlorophyll fluorescence parameters of plants under all light quality conditions were analyzed by using a linear regression model with other physiological and biochemical indexes. A significant correlation between non-photochemical quenching (NPQ) and leaf length was also observed. The content of chlorophyll b showed significant correlations with both root number and leaf number. Furthermore, chlorophyll a, along with its ratio to chlorophyll b, significantly correlated with root length. Chlorophyll b and the relative electron transport rate of PSII (ETRII) significantly correlated with root activity and the free proline content (FPC) and catalase (CAT) activity. The photochemical quenching coefficient (qP) significantly correlated with total soluble sugars content (SSC) and peroxidase (POD) activity. The correlation between the quantum yield of PSII (Fv/Fm ratio) and superoxide dismutase (SOD) activity was found to be significant. Similarly, the effective quantum yield of PSII photochemistry (ΦPSII) showed significant correlations with fresh weight, dry weight, soluble protein content (SPC), and ascorbate peroxidase (APX) activity. Through a principal component analysis (PCA), it was observed that plants cultivated under the 7R:3B light treatment achieved significantly better comprehensive scores compared to those grown under different light treatments. In conclusion, growth achieved under an LED emitting a ratio of 7R:3B light yielded the most robust Dendrobium hybrid plantlets within a controlled environment.

The evolving contribution of MRI measures towards the prediction of secondary progressive multiple sclerosis

BackgroundIn multiple sclerosis (MS), both lesion accrual and brain atrophy predict clinical outcomes. However, it is unclear whether these prognostic features are equally relevant throughout the course of MS. Among...