Clinical Practices Following Train-The-Trainer Trauma Course Completion in Uganda: A Parallel-Convergent Mixed-Methods Study.

BACKGROUND: Despite the growth of trauma training courses worldwide, evidence for their impact on clinical practice in low- and middle-income countries (LMICs) is sparse. We investigated trauma practices by trained providers in Uganda using clinical observation, surveys, and interviews. METHODS: Ugandan providers participated in the Kampala Advanced Trauma Course (KATC) from 2018 to 2019. Between July and September of 2019, we directly evaluated guideline-concordant behaviors in KATC-exposed facilities using a structured real-time observation tool. We conducted 27 semi-structured interviews with course-trained providers to elucidate experiences of trauma care and factors that impact adoption of guideline-concordant behaviors. We assessed perceptions of trauma resource availability through a validated survey. RESULTS: Of 23 resuscitations, 83% were managed without course-trained providers. Frontline providers inconsistently performed universally applicable assessments: pulse checks (61%), pulse oximetry (39%), lung auscultation (52%), blood pressure (65%), pupil examination (52%). We did not observe skill transference between trained and untrained providers. In interviews, respondents found KATC personally transformative but not sufficient for facility-wide improvement due to issues with retention, lack of trained peers, and resource shortages. Resource perception surveys similarly demonstrated profound resource shortages and variation across facilities. CONCLUSIONS: Trained providers view short-term trauma training interventions positively, but these courses may lack long-term impact due to barriers to adopting best practices. Trauma courses should include more frontline providers, target skill transference and retention, and increase the proportion of trained providers at each facility to promote communities of practice. Essential supplies and infrastructure in facilities must be consistent for providers to practice what they have learned.

A preliminary study on placental damage associated to experimental neosporosis in BALB/c mice.

Neospora caninum is a protozoan parasite which can infect a range of animals, including dogs, cattle, and sheep. Bovine neosporosis, which mainly causes abortion in cattle, results in substantial economic losses worldwide. To study the effects of N. caninum infection on the placenta, a pregnant mouse model for N. caninum infection was established. The litter size (8.6 ± 1.5) and the number of live pups (6.4 ± 1.8) of infected dams were significantly lower compared with those of non-infected dams. Trophoblast cell shrinkage and a large number of apoptosomes were detected in the placentas of the infected group. The parasite load in the placental tissue was significantly higher with time after infection. Likewise, apoptosis of placental trophoblast cells significantly increased with time after infection. Among the 66 apoptotic genes detected in this study, eight genes, including Bcl-2, were significantly differentially expressed by about > tenfold in infected and uninfected mice. The expression of BAX and tumor necrosis factor-alpha (TNF-α) was upregulated in the placental cells of the infected mice, whereas the expression of BCL-2 was downregulated. Enzyme-linked immunosorbent assays (ELISAs) showed that apoptotic protease caspase-3 level was significantly increased in placental cell suspension, and insulin-like growth factor (IGF)-2 level was significantly reduced. Acetylcholine (ACH) and placental prolactin (PL) levels were initially decreased but eventually increased. In summary, infection of mice with N. caninum caused apoptotic damage to the placental tissues, cells, and genes and affected the normal physiological functions of placenta, which may largely explain the adverse pregnancy outcomes caused by N. caninum infection in mice.

UFO-Net: A Linear Attention-Based Network for Point Cloud Classification.

Three-dimensional point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we designed an augmented sampling and grouping module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to extract point cloud's local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first tried to use a linearly normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module was adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that this method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which is 0.5% higher than PCT. Our network also achieved 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

Significant Liver Injury During Hospitalization for COVID-19 Is Not Associated With Liver Insufficiency or Death.

BACKGROUND & AIMS: Coronavirus-19 disease (COVID-19) is associated with hepatocellular liver injury of uncertain significance. We aimed to determine whether development of significant liver injury during hospitalization is related to concomitant medications or processes common in COVID-19 (eg, ischemia, hyperinflammatory, or hypercoagulable states), and whether it can result in liver failure and death. METHODS: There were 834 consecutive patients hospitalized with COVID-19 who were included. Clinical, medication, and laboratory data were obtained at admission and throughout hospitalization using an identified database. Significant liver injury was defined as an aspartate aminotransferase (AST) level 5 or more times the upper limit of normal; ischemia was defined as vasopressor use for a minimum of 2 consecutive days; hyperinflammatory state was defined as high-sensitivity C-reactive protein value of 100 mg/L or more, and hypercoagulability was defined as D-dimer 5 mg/L or more at any time during hospitalization. RESULTS: A total of 105 (12.6%) patients developed significant liver injury. Compared with patients without significant liver injury, ischemia (odds ratio [OR], 4.3; range, 2.5-7.4; P < .0001) and tocilizumab use (OR, 3.6; range, 1.9-7.0; P = .0001) were independent predictors of significant liver injury. Although AST correlated closely with alanine aminotransferase (R = 0.89) throughout hospitalization, AST did not correlate with the international normalized ratio (R = 0.10) or with bilirubin level (R = 0.09). Death during hospitalization occurred in 136 (16.3%) patients. Multivariate logistic regression showed that significant liver injury was not associated with death (OR, 1.4; range, 0.8-2.6; P = .2), while ischemic (OR, 2.4; range, 1.4-4.0; P = .001), hypercoagulable (OR, 1.7; range, 1.1-2.6; P = .02), and hyperinflammatory (OR, 1.9; range, 1.2-3.1; P = .02) disease states were significant predictors of death. CONCLUSIONS: Liver test abnormalities known to be associated with COVID-19 are secondary to other insults, mostly ischemia or drug-induced liver injury, and do not lead to liver insufficiency or death.

Prenatal exposure to airborne particulate matter of 1 µm or less and fetal growth: A birth cohort study in Beijing, China.

BACKGROUND: The association of airborne particulate matter of 1 µm or less (PM1) with fetal growth hasn't been studied. We aimed to investigate the association of PM1 with fetal growth parameters measured via ultrasonography and birth weight. METHODS: The birth cohort included 18,669 pregnant women who were pregnant between 2014 and 2017 in Tongzhou Maternal and Child Health Hospital of Beijing, China. The predicted PM1 concentration was matched with the residential addresses of each woman. The fetal abdominal circumference (AC), head circumference (HC), femur length (FL) and estimated fetal weight (EFW) were evaluated via ultrasonography, while birth weight was measured at birth. The fetal parameters and birth weight were standardized as gestational-age- and gender-adjusted Z-score. We defined undergrowth of fetal parameters, low birth weight (LBW) and small-for-gestational-age (SGA) as categorized outcomes. Generalized estimating equations and generalized linear regression were used to examine the associations of PM1 with quantitative and categorized outcomes, respectively. RESULTS: A 10 µg/m3 increase in PM1 was associated with decrement in the Z-scores of AC [-0.027, 95% confidence intervals (CI): -0.047~ -0.07]EFW (-0.055, 95%CI: -0.075~-0.035). These results remained robust after adjusting nitrogen dioxide and sulphur dioxide. We didn't observe significant results regarding the analyses of undergrowth of all fetal parameters and the analyses of birth weight outcomes. CONCLUSION: This study identified the negative associations between PM1 and fetal parameters in utero. The findings provided robust evidence that strategies for reducing PM1 exposure can prevent early-life health.

Detecting Eating Episodes From Wrist Motion Using Daily Pattern Analysis.

This paper presents new methods to detect eating from wrist motion. Our main novelty is that we analyze a full day of wrist motion data as a single sample so that the detection of eating occurrences can benefit from diurnal context. We develop a two-stage framework to facilitate a feasible full-day analysis. The first-stage model calculates local probabilities of eating P(Ew) within windows of data, and the second-stage model calculates enhanced probabilities of eating P(Ed) by treating all P(Ew) within a single day as one sample. The framework also incorporates an augmentation technique, which involves the iterative retraining of the first-stage model. This allows us to generate a sufficient number of day-length samples from datasets of limited size. We test our methods on the publicly available Clemson All-Day (CAD) dataset and FreeFIC dataset, and find that the inclusion of day-length analysis substantially improves accuracy in detecting eating episodes. We also benchmark our results against several state-of-the-art methods. Our approach achieved an eating episode true positive rate (TPR) of 89% with 1.4 false positives per true positive (FP/TP), and a time weighted accuracy of 84%, which are the highest accuracies reported on the CAD dataset. Our results show that the daily pattern classifier substantially improves meal detections and in particular reduces transient false detections that tend to occur when relying on shorter windows to look for individual ingestion or consumption events.

Odd-even effect in chiral side-chain cyanobiphenyl block copolymer assemblies prepared by polymerization-induced chiral self-assembly.

The precise control of the chirality of polymer assemblies is a challenge faced by scientists and has received significant attention in recent years. In this study, we employed the polymerization-induced chiral self-assembly (PICSA) method to create chiral side-chain cyanobiphenyl (CB) block copolymer (BCP) assemblies. The flexible spacers in chiral CB monomers were regulated to exhibit two distinct odd-even effects in the supramolecular asymmetrical arrangement of the CB mesogens inside BCP assemblies. The research results indicated that the liquid crystalline properties of CB mesogens significantly influence the magnitude and sign of their chiroptical properties. These findings have significant implications for the design of polymer assemblies with designable chiroptical functions.

Effect of dietary Eucommia ulmoides oliver polysaccharide on immune function and meat quality of Songliao Black Pigs.

Eucommia ulmoides is a traditional Chinese herbal medicine, with pharmacological effects such as lowering blood pressure and enhancing immune function. The effects of dietary Eucommia ulmoides polysaccharide (EUP) on immune function and meat quality were studied in Songliao Black Pigs. Blood lymphocyte counts and percentage, concentrations of serum total protein and of albumin increased, whereas those of urea nitrogen and triglyceride decreased. White blood cell and lymphocyte counts, and serum IgA, IgE, IgG2 a and IFN-γ increased. Average daily weight gain, slaughter weight, lean meat rate and cooked meat rate increased, whereas pH24, feed-weight ratio, fat rate, yellowness (b#) and centrifugal dehydration rate decreased. Transcriptome sequencing of longissimus dorsi muscle detected 32 differentially expressed genes (DEGs), of which 26 were up-regulated and 6 down-regulated. A total of 19 genes were differentially expressed in the four groups, 18 of which were up-regulated. The DEGs included ADAMTS4, PER1, STAC, SERPINE1, FASN, THRSP, SP7 and KRT80 and the protein interaction network showed 20 up-regulated nodes, three down-regulated nodes and 14 DEGs. GO functional annotation and enrichment analysis showed that 34 items were significantly enriched, including transferase activity, actin binding, acetyl coenzyme A, acyl coenzyme A metabolism, adipose tissue development and acyl glycerol homeostasis. KEGG pathway analysis showed that the AMPK and PPAR signaling pathways were enriched. Dietary Eucommia polysaccharide enhanced immune function in Songliao Black Pigs, improved growth and carcass performance, increased the expression of genes related to meat quality traits and improved meat quality.

Synthesis of Nucleotides Bearing the 2'-O-Trifluoromethyl Group and Their Application in RNA Analogs Preparation.

The integration of fluorine atoms into biologically active organic compounds has proved to be a vital technique in small molecule drugs. This technique can substantially enhance crucial properties, including metabolic stability, lipophilicity, and bioavailability, often with a mere addition of a single fluorine atom or a trifluoromethyl group. Over the past few decades, this concept has also been applied in nucleic acid chemistry. A commonly employed 2'-OH substitution is the introduction of a 2'-deoxy-2'-fluoro (2'-F) group. The strong electronegativity of fluorine prompts the modified siRNA to readily adopt a C3'-endo conformation, resulting in significant advantages in terms of binding affinity. To enrich the toolbox of chemical modification of oligonucleotides, the replacement of the 2'-OH with the 2'-O-trifluoromethyl group has been developed in RNA analog synthesis. Oligodeoxynucleotides containing the 2'-O-trifluoromethyl group can greatly increase the thermal stability of DNA/RNA duplexes depending on the position and amount of the modification. Moreover, 2'-O-trifluoromethylated oligodeoxynucleotide also exhibited a slightly higher resistance to snake venom phosphodiesterase than the unmodified oligodeoxynucleotide. The 2'-O-trifluoromethylated oligonucleotides can emerge as a label to study RNA structure and function as well, or to develop DNA/RNA-based diagnostics. Hence, it is necessary to report an effective method for the synthesis, deprotection, purification, and characterization of oligonucleotides bearing a 2'-O-trifluoromethyl group. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Preparation of 6-N-benzoyl-5'-O-dimethoxytrityl-2'-O-trifluoromethyl adenosine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 2: Preparation of 4-N-acetyl-5'-O-dimethoxytrityl-2'-O-trifluoromethyl cytidine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 3: Preparation of 2-N-isobutyryl-5'-O-dimethoxytrityl-2'-O-trifluoromethyl guanine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 4: Preparation of 5'-O-dimethoxytrityl-2'-O-2-trifluoromethyl uridine 3'-(2-cyanoethyl N,N-diisopropyl) phosphoramidite Basic Protocol 5: Solid-phase synthesis of 2'-O-trifluoromethylated RNA analogs Basic Protocol 6: Deprotection and purification of 2'-O-trifluoromethyl-RNAs.

Protective effect of Inonotus obliquus polysaccharide on mice infected with Neospora caninum.

The study aimed to explore the protective effects of Inonotus obliquus polysaccharide (IOP) on Neospora caninum (N. caninum) infection. Our data showed that the survival rate of the mice was the highest and the survival time was the longest when the IOP was 2 mg/10 g. In agreement with these observations, IOP alleviated the pathological damage in the various organs and tissues of the mice. Compared with that in the Neosporidium infection model group, the content of N. caninum in the heart, liver, spleen, lung, kidney and brain, determined through HE staining, was significantly lower. In addition, IOP inhibited the levels of immunoglobulin G1 (IgG1) and immunoglobulin G2 (IgG2a) from the 21st to 42nd day of the administration group, whereas the levels of interleukin-12 (IL-12) and serum tumor necrosis factor alpha (TNF-α) were down-regulated at 7 d - 42 d. The production of CD4+ T lymphocytes was promoted, the number of CD8+ T lymphocytes were significantly lower and the CD4+/CD8+ ratio was significantly elevated. Furthermore, IOP effectively balanced the levels of hormones including gonadotropin-releasing hormone (GnRH), luteotropic hormone (LH) and testosterone (T) in male mice, and progesterone (PROG), estradiol (E2) and prolactin (PRL) in female mice. These findings demonstrate that IOP exerts protective effects against pathological damage caused by N. caninum infection in mice, and improve the immune function of the organism and regulate the secretion balance of sex hormones.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge.

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway structures remains prohibitively time-consuming. While significant efforts have been made towards enhancing automatic airway modelling, current public-available datasets predominantly concentrate on lung diseases with moderate morphological variations. The intricate honeycombing patterns present in the lung tissues of fibrotic lung disease patients exacerbate the challenges, often leading to various prediction errors. To address this issue, the 'Airway-Informed Quantitative CT Imaging Biomarker for Fibrotic Lung Disease 2023' (AIIB23) competition was organized in conjunction with the official 2023 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). The airway structures were meticulously annotated by three experienced radiologists. Competitors were encouraged to develop automatic airway segmentation models with high robustness and generalization abilities, followed by exploring the most correlated QIB of mortality prediction. A training set of 120 high-resolution computerised tomography (HRCT) scans were publicly released with expert annotations and mortality status. The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients. The results have shown that the capacity of extracting airway trees from patients with fibrotic lung disease could be enhanced by introducing voxel-wise weighted general union loss and continuity loss. In addition to the competitive image biomarkers for mortality prediction, a strong airway-derived biomarker (Hazard ratio>1.5, p < 0.0001) was revealed for survival prognostication compared with existing clinical measurements, clinician assessment and AI-based biomarkers.

PM2.5-related neonatal encephalopathy due to birth asphyxia and trauma: a global burden study from 1990 to 2019.

Long-term exposure to fine particulate matter (PM2.5) may increase the risk of neonatal encephalopathy due to birth asphyxia and trauma. However, little is known about the trends of PM2.5-related neonatal encephalopathy burden under different levels of social and economic development. We studied the burden of PM2.5-related neonatal encephalopathy due to birth asphyxia and trauma measured by the age-standardized mortality rate (ASMR) and the age-standardized disability-adjusted life years rate (ASDR), and its trends with the socio-demographic index (SDI) in 192 countries and regions from 1990 to 2019. This is a retrospective study using the Global Burden of Disease Study 2019 (GBD2019) database. The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) are used to measure the burden of PM2.5-related neonatal encephalopathy in different countries and regions. The mortality rate (per 100 thousand) is used to evaluate the differences of PM2.5-related neonatal encephalopathy burden in sex and age. The annual percentage changes (APCs) and the average annual percentage changes (AAPCs) are used to reflect the trends of PM2.5-related neonatal encephalopathy burden over years (1990-2019) and are calculated using a Joinpoint model. The relationship of the socio-demographic index with the ASMR and ASDR is calculated using Gaussian process regression. In summary, the global burden of PM2.5-related neonatal encephalopathy increased since 1990, especially in boys, early neonates, and regions with low-middle SDI. Globally, the ASMR and ASDR of PM2.5-related neonatal encephalopathy burden in 2019 were 0.59 (95% CI: 0.40, 0.83) per 100,000 people and 52.59 (95% CI: 35.33, 73.67) per 100,000 people, respectively. From 1990 to 2019, the ASMR and ASDR of PM2.5-related neonatal encephalopathy increased by 44.39% and 44.19%, respectively. The global average annual percentage changes of ASMR and ASDR were 1.3 (95% CI: 1.0, 1.6). The relationship between the socio-demographic index and the burden of PM2.5-related neonatal encephalopathy presented negative correlation when the socio-demographic index was more than 0.60. Middle, high-middle, and high SDI regions had decreasing trends of PM2.5-related neonatal encephalopathy, of which the AAPCs for both ASMR and ASDR ranged from - 0.3 to - 3.1. Besides improving the progress in national policy and the coverage rate of maternal and neonatal health care and facility-based delivery, air pollution control may also be a better way for countries with large and increasing amounts of exposure to PM2.5 pollution to reduce neonatal encephalopathy. And our results also suggest that low and low-middle SDI countries should appropriately pay more attention to early newborns and boys.

Adversarial Transformer for Repairing Human Airway Segmentation.

Automated airway segmentation models often suffer from discontinuities in peripheral bronchioles, which limits their clinical applicability. Furthermore, data heterogeneity across different centres and pathological abnormalities pose significant challenges to achieving accurate and robust segmentation in distal small airways. Accurate segmentation of airway structures is essential for the diagnosis and prognosis of lung diseases. To address these issues, we propose a patch-scale adversarial-based refinement network that takes in preliminary segmentation and original CT images and outputs a refined mask of the airway structure. Our method is validated on three datasets, including healthy cases, pulmonary fibrosis, and COVID-19 cases, and quantitatively evaluated using seven metrics. Our method achieves more than a 15% increase in the detected length ratio and detected branch ratio compared to previously proposed models, demonstrating its promising performance. The visual results show that our refinement approach, guided by a patch-scale discriminator and centreline objective functions, effectively detects discontinuities and missing bronchioles. We also demonstrate the generalizability of our refinement pipeline on three previous models, significantly improving their segmentation completeness. Our method provides a robust and accurate airway segmentation tool that can help improve diagnosis and treatment planning for lung diseases.

A Convenient Method for the Synthesis of 2'-O-Cyanoethylated Nucleotides and Their Application in the Solid-Phase Synthesis of Related RNA Analogs.

Although small interfering RNA (siRNA) is a key player among gene inhibition therapeutics, there are many obstacles to the development of siRNA drugs due to inherent properties of oligonucleotides, including the unsatisfactory stability of unmodified siRNA, poor pharmacokinetic distribution, and the toxicity induced by off-target effects. To maximize treatment potency, chemical modification of siRNA has undoubtedly been the most successful strategy by far. Widely applied modifications include phosphorothioate linkages, 2'-O-methyl modifications, and 2'-fluoro modifications, among others. To extend the family of chemical modifications for oligonucleotides, 2'-O-cyanoethylated RNA analogs were developed through the replacement of the 2'-hydroxyl group with a 2'-O-cyanoethyl group (-OCH2 CH2 CN). This modification can provide several advantages over unmodified RNA, such as increased stability, improved binding affinity to complementary DNA or RNA strands, and resistance to degradation by cellular nucleases. The 2'-O-cyanoethyl-modified RNAs not only are applied in RNA silencing machinery but also act as research tools for studying RNA structure and function or for developing RNA-based diagnostics. Therefore, the efficient synthesis, deprotection, purification, and characterization of 2'-O-cyanoethylated RNAs deserves more attention. This protocol describes the chemical synthesis of 2'-O-cyanoethylated nucleotides and the solid-phase synthesis, deprotection, and purification of 2'-O-cyanoethylated RNAs. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Preparation of 6-N-dimethylformamidyl-5'-O-dimethoxytrityl-2'-O-cyanoethyl adenosine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 2: Preparation of 4-N-acetyl-5'-O-dimethoxytrityl-2'-O-cyanoethyl cytidine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 3: Preparation of 2-N-dimethylformamidyl-5'-O-dimethoxytrityl-2'-O-cyanoethyl guanine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 4: Preparation of 5'-O-dimethoxytrityl-2'-O-2-cyanoethyl uridine 3'-(2-cyanoethyl N,N-diisopropyl)phosphoramidite Basic Protocol 5: Solid-phase synthesis of 2'-O-cyanoethylated RNA analogs Basic Protocol 6: Deprotection and purification of synthesized 2'-O-cyanoethyl-RNAs.

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation.

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have proposed methods to automatically segment airways from computerized tomography (CT) images. However, some small-sized airway branches (e.g., bronchus and terminal bronchioles) significantly aggravate the difficulty of automatic segmentation by machine learning models. In particular, the variance of voxel values and the severe data imbalance in airway branches make the computational module prone to discontinuous and false-negative predictions, especially for cohorts with different lung diseases. The attention mechanism has shown the capacity to segment complex structures, while fuzzy logic can reduce the uncertainty in feature representations. Therefore, the integration of deep attention networks and fuzzy theory, given by the fuzzy attention layer, should be an escalated solution for better generalization and robustness. This article presents an efficient method for airway segmentation, comprising a novel fuzzy attention neural network (FANN) and a comprehensive loss function to enhance the spatial continuity of airway segmentation. The deep fuzzy set is formulated by a set of voxels in the feature map and a learnable Gaussian membership function. Different from the existing attention mechanism, the proposed channel-specific fuzzy attention addresses the issue of heterogeneous features in different channels. Furthermore, a novel evaluation metric is proposed to assess both the continuity and completeness of airway structures. The efficiency, generalization, and robustness of the proposed method have been proved by training on normal lung disease while testing on datasets of lung cancer, COVID-19, and pulmonary fibrosis.

The Association between the Burden of PM2.5-Related Neonatal Preterm Birth and Socio-Demographic Index from 1990 to 2019: A Global Burden Study.

BACKGROUND: Preterm birth (PTB) leads to short-term and long-term adverse effects on newborns. Exposure to fine particulate matter (PM2.5) was positively related to PTB. However, the global annual average PM2.5 was three times than the recommended value in 1998-2014. Socio-demographic index (SDI) is a new indicator that comprehensively reflects the overall development level of a country, partly because of "the epidemiological transition". Among other countries with higher and similar SDI levels, policy makers have the opportunity to learn from their successful experiences and avoid their mistakes by identifying whether their burdens of disease are higher or lower than the expected. However, it is unclear about the trends of the burden of PM2.5-related preterm birth in different countries and different levels of SDI regions. Additionally, the relationship between the SDI and the burden in 1990-2019 is also unclear. METHODS: This was a retrospective study based on the Global Burden of Disease Study 2019 (GBD2019) database from 1990 to 2019. The burden of PM2.5-related PTB was measured by the age-standardized mortality rate (ASMR), age-standardized disability-adjusted life years rate (ASDR), mortality rate, and the disability-adjusted life years (DALYs). The annual percentage changes (APCs) and the average annual percentage changes (AAPCs) were used to reflect the trends over the past 30 years, which were calculated using a joinpoint model. The relationships between the ASMR, ASDR, and SDI were calculated using a Gaussian process regression. FINDINGS: In 2019, the entire burden of PM2.5-related PTB was relatively high, where the ASMR and the ASDR were 0.76 and 67.71, increasing by 7.04% and 7.12%, respectively. It mainly concentrated on early neonates, boys, and on low-middle SDI regions. The increase in the burden of PM2.5-related PTB in low and low-middle SDI regions is slightly higher than the decrease in other SDI regions. In 2019, the burden varied greatly among different levels of SDI regions where ASMRs varied from 0.13 in high SDI regions to 1.19 in low-middle regions. The relationship between the expected value of the burden of PM2.5-related PTB and SDI presented an inverted U-shape, and it reached the maximum when SDI is around 0.50. The burdens in four regions (South Asia, North Africa and the Middle East, western sub-Saharan Africa, and southern sub-Saharan Africa) were much higher than the mean value. Boys bore more burden that girls. The sex ratio (boys:girls) of the burden showed a dramatically increasing trend in low SDI regions and a decreasing trend in middle SDI regions and high-middle SDI regions. These differences reflect the huge inequality among regions, countries, ages, and sex in the burden of PM2.5-related PTB. CONCLUSION: The overall burden of PM2.5-related PTB in 2019 was relatively high, mainly concentrated on early neonates, boys, and on low-middle SDI regions. It showed an increasing trend in low-middle and low SDI regions. The association between the burden and the SDI presented an inverted U-shape. It is very necessary to promulgate policies to prevent and control air pollution in countries with large and increasing exposure to PM2.5 pollution because it does not need action at an individual level. Focusing on public educational interventions, public and professional policies, and improving accessibility of prenatal care are other feasible ways for low and low-middle SDI countries. Policy makers should also appropriately allocate medical resources to boys and early newborns.

PM2.5-Related Neonatal Infections: A Global Burden Study from 1990 to 2019.

BACKGROUND: Long-term exposure to fine particulate matter (PM2.5) may increase the risk of neonatal infections. To show the effects of PM2.5 on neonatal infections as well as the trends of the effect, we studied the burden measured by the age-standardized mortality rate (ASMR) and the age-standardized disability-adjusted life years rate (ASDR) and its trends with the socio-demographic index in 192 countries and regions from 1990 to 2019. METHODS: This is a retrospective study that uses the Global Burden of Disease Study 2019 database. The age-standardized mortality rate and age-standardized disability-adjusted life years rate are used to measure the burden of PM2.5-related neonatal infections in different countries and regions. The annual percentage changes and the average annual percentage changes are used to reflect the trends over the years (1990-2019) and are calculated using a Joinpoint model. The relationship of the socio-demographic index with the ASMR and ASDR is calculated and described using Gaussian process regression. RESULTS: With the rapid increase in the global annual average of PM2.5, the global burden of PM2.5-related neonatal infections has increased since 1990, especially in early neonates, boys, and low-middle SDI regions. Globally, the ASMR and ASDR of PM2.5-related neonatal infections in 2019 were 0.21 (95% CI: 0.14, 0.31) and 19.06 (95% CI: 12.58, 27.52) per 100,000 people, respectively. From 1990 to 2019, the ASMR and ASDR increased by 72.58% and 73.30%, and their average annual percentage changes were 1.9 (95% CI: 1.3, 2.6) and 2.0 (95% CI: 1.3, 2.6), respectively. When the socio-demographic index was more than 0.60, it was negatively related to the burden of PM2.5-related neonatal infections. Surprisingly, the burden in low SDI regions was lower than it was in low-middle and middle SDI regions, while high-middle and high-SDI regions showed decreasing trends. INTERPRETATION: Boys bore a higher PM2.5-related neonatal burden, with male fetuses being more likely to be affected by prenatal exposure to PM2.5 and having less of a biological survival advantage. Poverty was the root cause of the burden. Higher SDI countries devoted more resources to improving air quality, the coverage of medical services, the accessibility of institutional delivery, and timely referral to reduce the disease burden. The burden in low SDI regions was lower than that in low-middle and middle SDI regions. One reason was that the benefits of medical services were lower than the harm to health caused by environmental pollution in low-middle and middle SDI regions. Moreover, the underreporting of data is more serious in low SDI countries. CONCLUSIONS: In the past 30 years, the global burden of PM2.5-related neonatal infections has increased, especially in early neonates, boys, and low-middle SDI regions. The huge difference compared to higher SDI countries means that lower SDI countries have a long way to go to reduce the disease burden. Policy makers should appropriately allocate medical resources to boys and early newborns and pay more attention to data under-reporting in low SDI countries. In addition, it is very necessary to promulgate policies to prevent and control air pollution in countries with large and increasing exposure to PM2.5 pollution.

Human treelike tubular structure segmentation: A comprehensive review and future perspectives.

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal blood vessels, and hepatic blood vessels. Large collections of 2D and 3D images have been made available by medical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), Optical coherence tomography (OCT) and ultrasound in which the spatial arrangement can be observed. Segmentation of these structures in medical imaging is of great importance since the analysis of the structure provides insights into disease diagnosis, treatment planning, and prognosis. Manually labelling extensive data by radiologists is often time-consuming and error-prone. As a result, automated or semi-automated computational models have become a popular research field of medical imaging in the past two decades, and many have been developed to date. In this survey, we aim to provide a comprehensive review of currently publicly available datasets, segmentation algorithms, and evaluation metrics. In addition, current challenges and future research directions are discussed.

Splenic Abscess in the New Millennium: A Descriptive, Retrospective Case Series.

Background: Splenic abscess is a rare infection often resulting from hematogenous spread. Immunocompromised states are commonly comorbid, and the microbiology is heterogeneous. Methods: We conducted a retrospective review of 33 cases identified by convenience sampling. Cases were treated in our institution's hospital system between May 2012 and February 2021 and classified as proven or probable based on predetermined criteria. Results: The median age was 57 years, and 58% were men. Common underlying diseases included diabetes mellitus (30%), pancreatic disease (30%), and hematological malignancy (15%). The most common mechanism of pathogenesis was hematogenous spread (n = 13). Escherichia coli, enterococcal spp., and anaerobes were frequently implicated. One case was discovered at autopsy and excluded from subsequent analyses. The median duration of antimicrobial therapy (range) was 45 (5-525) days, and the median length of index hospitalization was 20 days. Percutaneous drainage by interventional radiology was common (17 of 32; 53%), and 6 patients underwent splenectomy. Treatment success was achieved in 14 of 32 cases (44%), with clinical stability in 3 of 32 cases (9%). Failures occurred in 13 of 32 (41%) cases, 2 of whom died from splenic abscesses. Two patients (2 of 32) were lost to follow-up. Conclusions: To our knowledge, this is the largest North American series since the turn of the century and the first to distinguish between proven and probable cases. As reflected in our series, patients with splenic abscess may require prolonged hospitalizations and courses of antimicrobial therapy. Improvements in management are needed.

Development and Validation of Multi-Stage Prediction Models for Pre-eclampsia: A Retrospective Cohort Study on Chinese Women.

Objective: The aim of this study is to develop multistage prediction models for pre-eclampsia (PE) covering almost the entire pregnancy period based on routine antenatal measurements and to propose a risk screening strategy. Methods: This was a retrospective cohort study that included 20582 singleton pregnant women with the last menstruation between January 1, 2013 and December 31, 2019. Of the 20582 women, 717 (3.48%) developed pre-eclampsia, including 46 (0.22%) with early-onset pre-eclampsia and 119 (0.58%) preterm pre-eclampsia. We randomly divided the dataset into the training set (N = 15665), the testing set (N = 3917), and the validation set (N = 1000). Least Absolute Shrinkage And Selection Operator (LASSO) was used to do variable selection from demographic characteristics, blood pressure, blood routine examination and biochemical tests. Logistic regression was used to develop prediction models at eight periods: 5-10 weeks, 11-13 weeks, 14-18 weeks, 19-23 weeks, 24-27 weeks, 28-31 weeks, 32-35 weeks, and 36-39 weeks of gestation. We calculated the AUROC (Area Under the Receiver Operating Characteristic Curve) on the test set and validated the screening strategy on the validation set. Results: We found that uric acid tested from 5-10 weeks of gestation, platelets tested at 18-23 and 24-31 weeks of gestation, and alkaline phosphatase tested at 28-31, 32-35 and 36-39 weeks of gestation can further improve the prediction performance of models. The AUROC of the optimal prediction models on the test set gradually increased from 0.71 at 5-10 weeks to 0.80 at 24-27 weeks, and then gradually increased to 0.95 at 36-39 weeks of gestation. At sensitivity level of 0.98, our screening strategy can identify about 94.8% of women who will develop pre-eclampsia and reduce about 40% of the healthy women to be screened by 28-31 weeks of pregnancy. Conclusion: We developed multistage prediction models and a risk screening strategy, biomarkers of which were part of routine test items and did not need extra costs. The prediction window has been advanced to 5-10 weeks, which has allowed time for aspirin intervention and other means for PE high-risk groups.