Concentration identification and endpoint-oriented health risk assessments on a broad-spectrum of organic compounds in atmospheric fine particles: A sampling experimental study in Beijing, China

Understanding the complicate chemical components in atmospheric fine particulate matter (PM2.5) helps policy makers for pollutants control track progress and identify disparities in overall health risks. However, till now, information on accurate component detection, source identification, and effect-oriented risk assessment is scarce, especially for the simultaneous analysis of a broad-spectrum of compounds. In this study, a high-throughput target method was employed to distinguish the occurrence and characteristics of 152 chemicals: phthalate esters (PAEs), organophosphate esters (OPEs), carboxylic acid esters (CAEs), nitrophenols (NPs), nitrogen heterocyclic compounds (NHCs), per- and poly-fluoroalkyl substances (PFASs), triclosan and its derivatives (TCSs), and organosulfates (OSs) in ambient PM2.5 collected from Beijing, China. Detection frequencies of 77 targeted compounds were >50 %. Total concentrations of all compounds ranged from 33.1 to 745 ng/m3. The median concentration of ∑PAEs (108 ng/m3) was the highest, followed by ∑CAEs (12.2 ng/m3) and ∑NPs (10.1 ng/m3). Organophosphate diesters (di-OPEs) and TCSs were reported for the first time in ambient PM2.5. The pollutants mainly originated from the local industrial production, release of building materials, and environmental degradation of parent compounds. Based on absorption, distribution, metabolism, excretion, and toxicity (ADMET)-oriented risk evaluations, we found that bis (2-ethylhexyl) phthalate, diisobutyl phthalate, dibutyl phthalate, and di (2-ethylhexyl) adipate have high health risks. Additionally, the high oxidative stress potential of 4-nitrocatechol and the strong blood-brain barrier penetration potential of triclosan cannot be ignored. Our study will facilitate the evaluations of specific health outcomes and mechanisms of pollutants, and suggestion of pollutants priority control to reduce human health hazards caused by atmospheric particles.

[Progress in pathophysiology research and update on diagnosis and treatment strategies for fecal incontinence]

The traditional barrier theory believes that fecal incontinence is related to an imbalance of the recto-anal barrier and the characteristics of stool. However, in clinical practice this theory proves unable to explain all types of fecal incontinence. In recent years, research on the mechanisms related to fecal incontinence has shifted to a new integrative concept with the rectum and anus as functional units, and the central-peripheral nervous system and internal and external anal sphincters as a control loop. The diagnosis and treatment strategy of fecal incontinence, which is replaced by sacral neuromodulation, is undergoing a quiet change. With the progressively aging population in China, the need to improve the diagnosis and treatment of fecal incontinence has become increasingly urgent. This article explores the trends in diagnosis and treatment and mechanism research from the perspective of recent advances in pathophysiological research and updated diagnosis and treatment methods for fecal incontinence.

[A follow-up study on the pain changes trend and effects in patients diagnosed with herpes zoster in Beijing City]

Objective: To understand the changes in pain and its effects in patients with the diagnosis of herpes zoster. Methods: A total of 3 487 patients diagnosed with herpes zoster (HZ) for the first time at the outpatient department of Miyun District Hospital from January 1, 2017, to December 31, 2019, were included in the study. The information of patients was registered and issued with a record card. Patients were required to record the time of pain and rash by themselves. Telephone follow-up was conducted at 21, 90, 180 and 365 days after the onset of rashes, including hospitalization, location of rash and pain, and the time of start and end. The impact of pain on life was evaluated by the Zoster Brief Pain Inventory (ZBPI). Results: The age of 2 999 HZ patients included in the analysis were (53±16) years old, including 1 377 (45.91%) males and 1 903 (63.45%) patients aged 50 years and older. After 21 days of rash, mild, moderate and severe pain accounted for 20.87% (626 cases), 37.98% (1 139 cases) and 33.81% (1 014 cases), respectively. Only 5.07% (152 cases) had no pain or discomfort, and 2.27% (68 cases) had no pain but discomfort. Most of the pain sites were consistent with the rash sites. The chest and back and waist and abdomen were the most common, accounting for 35.58% (1 067 cases) and 29.18% (875 cases), respectively, followed by the limbs and face and neck, accounting for 16.74% (502 cases) and 16.40% (492 cases), respectively. The M (Q1, Q3) of pain days in the HZ patients was 14 (8, 20) days, and the incidence of post-herpetic neuralgia (PHN) was 6.63% (171/2 580) (excluding 419 patients who refused to visit or lost to visit on 90 days after the onset of rash). The pain score of HZ patients within 21 days after the rash was (5.19±2.73) points, and the pain score of PHN patients was (7.61±2.13) points, which was significantly higher than that of non-PHN patients [(5.04±2.69) points] (P<0.001). Daily activities, emotions, walking ability, work, social interaction, sleep and recreation were affected for 21 days after the rash in HZ patients, ranging from 60.79% to 83.83%, with sleep being the most affected (83.83%). The impact scores of pain and life dimensions in PHN patients ranged from 4.59 to 7.61 points on the ZBPI scale, which were higher than those in non-PHN patients (2.49-5.04) (t values ranged from 8.86 to 11.67, all P values <0.001). Conclusion: The proportion of pain in HZ patients after the diagnosis is high, and the pain is more obvious in patients with PHN and HZ patients aged 50 and older, which has a greater impact on their daily lives.

Polyglucosan body density in the aged mouse hippocampus is controlled by a novel modifier locus on chromosome 1

Aging can be associated with the accumulation of hypobranched glycogen molecules (polyglucosan bodies, PGBs), particularly in astrocytes of the hippocampus. While PGBs have a detrimental effect on cognition in diseases such as adult polyglucosan body disease and Lafora disease, the underlying mechanism and clinical relevance of age-related PGB accumulation remains unknown. Here, we have investigated the genetic basis and functional impact of age-related PGB accumulation in 32 fully sequenced BXD-type strains of mice which exhibit a 400-fold variation in PGB burden in 16-18 month old females. We mapped a major locus controlling PGB density in the hippocampus to chromosome 1 at 72-75 Mb (linkage of 4.9 -logP), which we defined as the Pgb1 locus. To identify potentially causal gene variants within Pgb1, we generated extensive hippocampal transcriptome datasets and identified two strong candidate genes for which mRNA correlates with PGB density-Smarcal1 and Usp37. In addition, both Smarcal1 and Usp37 contain non-synonymous allele variations likely to impact protein function. A phenome-wide association analysis highlighted a trans-regulatory effect of the Pgb1 locus on expression of Hp1bp3, a gene known to play a role in age-related changes in learning and memory. To investigate the potential impact of PGBs on cognition, we performed conditioned fear memory testing on strains displaying varying degrees of PGB burden, and a phenome-wide association scan of ~12,000 traits. Importantly, we did not find any evidence suggesting a negative impact of PGB burden on cognitive capacity. Taken together, we have identified a major modifier locus controlling PGB burden in the hippocampus and shed light on the genetic architecture and clinical relevance of this strikingly heterogeneous hippocampal phenotype.

Bisphenol analogues induce thyroid dysfunction via the disruption of the thyroid hormone synthesis pathway

Bisphenol analogues are widely used in industrial and daily-use consumer products having imperfect thyroid hormones (THs) structures. Widespread exposure interferes with thyroid-related health outcomes in human. The mechanisms of disruption on TH synthesis and subsequent thyroid dysfunction by different bisphenol analogues remain unclear. Here, we evaluated bisphenol-induced thyroid endocrine disruption in C57BL/6 mice at doses of 0.002, 0.02, 2, and 20 mg/kg body weight/day (BW/d) for five consecutive weeks. Administration of 20 mg/kg BW/d bisphenol S (BPS) and 2 mg/kg BW/d tetrabromobisphenol S (TBBPS) significantly increased serum thyrotropin (TSH) levels to 1.21-fold and 1.20-fold of control group, respectively, indicating that bisphenols induced thyroid dysfunction in mice. Height of the thyroid follicle epithelium significantly increased to 1.27-, 1.24-, 1.26-, and 1.36-fold compared to control group with BPA, BPS, TBBPA, and TBBPS at 20 mg/kg BW/d, respectively, indicating impairment of the thyroid gland structure, and TBBPS showed potent effect. Exposure to bisphenol analogues of 0.02 mg/kg BW/d downregulated the protein expression levels of thyrotropin receptor, the sodium/iodide symporter, thyroperoxidase. The TH-dependent effects were further determined using the T-Screen assay at 10-11 M to 10-5 M concentrations. Bisphenol analogues significantly decreased TH-dependent GH3 cell proliferation, indicating the antagonistic activity of bisphenol analogues. The gene responsible for THs synthesis of thyrotropin releasing hormone receptor and TSH were upregulated, but downregulation of thyroid receptor β was observed. Our results suggest that bisphenol analogues distinctly induce thyroid dysfunction via TH synthesis, implying adverse effect of bisphenol analogues on TH homeostasis and subsequent physiological processes.

Associations of cadmium exposure with risk of metabolic syndrome and its individual components: a meta-analysis

Data directly associating cadmium (Cd) with metabolic syndrome (MetS) are sparse and inconsistent. We aimed to quantitatively assess the association of Cd exposure with risk of MetS and its individual components. Literature searching was performed in PubMed, EMBASE, and MEDLINE-OVID through September, 2021. Weighted odds ratios (ORs) for MetS and its components were pooled by comparing the highest to the lowest category of Cd exposure using random-effects models. Eleven (10 from Asia and 1 from the US) cross-sectional studies (33,887 participants and 7176 cases) were identified. Overall, Cd exposure was not associated with risk of MetS [OR: 1.08, 95% confidence interval (CI): 0.92, 1.28]. However, the association became significant when pooling Asian studies (OR: 1.18, 95% CI: 1.02, 1.35), and it was more pronounced with Cd measured in blood (OR: 1.24, 95% CI: 1.05, 1.45). Additionally, Cd exposure was significantly associated with reduced HDL-cholesterol (OR: 1.27, 95% CI: 1.05, 1.54) and elevated triglyceride (OR: 1.17, 95% CI: 1.05, 1.30), but not other components. This meta-analysis indicates that Cd exposure is associated with risk of MetS among Asian populations, which is mainly explained by Cd's association with dyslipidemia. Further studies are needed to better understand the mechanism of action.

Smoking Modifies the Association Between Radon Exposure and Incident Ischemic Stroke: The REGARDS Study

BACKGROUND

Exposure to radon has been linked to lung cancer and other lung diseases. Although biologically plausible, research of residential radon exposure in relation to stroke risk is scarce.

METHODS

Study participants were from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) cohort (n=30 239), which consisted of male and female non-Hispanic Black and White adults aged 45 and older. After excluding participants with baseline stroke and transient ischemic attack, and missing information on exposure and outcome of interest, the final sample size was 26 950. The primary outcome was time to the first ischemic stroke through September 30, 2020. County-level radon measures from Lawrence Berkeley National Laboratory were linked to each participant based on their geocoded residential history. We used Cox proportional hazards regression models with a time-dependent exposure to estimate hazard ratios and 95% CIs for the association.

RESULTS

After controlling for potential confounding factors including demographic, lifestyle, clinical variables, and PM2.5, radon exposure was significantly associated with incident ischemic stroke among never-smokers (hazard ratio, 1.39 [95% CI, 1.01-1.90]) but not ever-smokers. The results were generally consistent in the sensitivity analysis when using radon measures from state/Environmental Protection Agency residential radon survey.

CONCLUSIONS

Findings from this study suggest that the association between residential radon exposure and incidence of ischemic stroke varies by smoking status and may be prominent in never-smokers. Further studies incorporating indoor-radon measures are needed to confirm these findings.

[Mediating effects of obesity and metabolic factors in hyperuricemia and prehypertension]

Objective: To assess the mediating effects of obesity and metabolic factors in the relationship between hyperuricemia (HUA) and prehypertension. Methods: A total of 9 399 individuals were selected using a multistage stratified whole-group random sampling method from 90 villages (neighborhood committees) in 30 towns (streets) of 5 districts (counties) in Fuzhou. A total of 4 754 study subjects were included. A linear regression model was used to analyze the association of HUA with obesity and metabolic factors. Single-factor and multi-factor logistic regression models were used to analyze the association of HUA, obesity, and metabolic factors with prehypertension. Mediating effects models were used to analyze the mediating effects of obesity and metabolic factors on the association between HUA and prehypertension. Results: After adjusting for confounders, the association between HUA and cholesterol, triglycerides, HDL-C, LDL-C, BMI, waist circumference, creatinine, and urea nitrogen were significantly correlated (P<0.001). HUA, waist circumference, BMI, and triglycerides were significantly associated with prehypertension (P<0.001). Waist circumference, BMI, and triglycerides mediated the relationship between HUA and prehypertension, with OR (95%CI) of 1.018 (1.007-1.027), 1.010 (1.002-1.018), and 1.010 (1.003-1.017) (P<0.001), with mediating proportions of 7.76%, 4.31%, and 4.31% respectively. No mediating effect of cholesterol, HDL-C, LDL-C, creatinine, and urea nitrogen was found on the relationship (P>0.05). Conclusions: Waist circumference, BMI, and triglycerides all had mediating effects in the association between HUA and prehypertension. For the general population, weight control, waist circumference, and a high-fat diet should be used to reduce the occurrence of prehypertension.

Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

A Novel Strategy to Enhance Radiotherapy Efficacy: Results from the Prospective Phase I Clinical Trial of MR-Guided Focused Ultrasound-Stimulated Microbubbles (MRgFUS+MB) Treatment for Breast Cancer

PURPOSE/OBJECTIVE(S)

Preclinical in vitro and in vivo studies have demonstrated that tumor cell death can be enhanced 10- to 40-fold when radiotherapy (RT) is combined with focused-ultrasound (FUS)-stimulated microbubbles (MB) treatment. MBs are gas microspheres used as intravascular contrast agents. The acoustic exposure of MBs within the target volume causes bubbles cavitation that induces perturbation of tumor vasculature. This activates apoptotic pathways responsible for the ablative effect of stereotactic body radiotherapy, which would otherwise require high-dose radiotherapy (>8-10 Gy/fraction) to be activated. Subsequent irradiation of an MB-sensitized tumor causes increased anoxic tumor killing, which occurs in addition to canonical RT-induced DNA damage. Given the compelling results of preclinical data, we conducted a phase I clinical trial of magnetic resonance (MR)-guided FUS-stimulated MBs (MRgFUS+MB) treatment for breast cancer patients (pts). We report the safety and efficacy results of this new radio enhancement treatment.

MATERIALS/METHODS

This is a single-center, single-arm, investigator-initiated phase 1 clinical trial (NCT04431674). We included pts with stage I-IV breast cancer with tumor in situ for whom breast or chest wall RT was deemed adequate by a multidisciplinary team. Pts were excluded if they had contraindications for contrast-enhanced MR or MB administration. Pts underwent 2-3 MRgFUS+MB treatments throughout the RT course. We used an MR-coupled FUS-device operating at 500 KHz and 540 kPa peak negative pressure to deliver the treatment. The FUS sonicated intravenously administrated MB within the MR-guided target volume. Pts were monitored for 30-min post-procedure and subsequently treated with RT. The primary outcome was acute toxicity per Common Terminology for Adverse Events V5.0. Secondary outcomes were radiological response at 3 months and local control (LC) at 1 year. Kaplan-Meier method was used to estimate local control. All pts signed a written consent form before study participation.

RESULTS

We enrolled 18 females with 20 primary breast cancer treated with MRgFUS+MB therapy. The median age was 60 years (range, 44-90). The molecular subtypes consisted of basal-like (n = 3/20), luminal (n = 11/20), and HER2-enriched (n = 6/20). The prescribed dose was 20 Gy/5 fractions (n = 8/20), 30-35 Gy/5 fractions (n = 7/20), 30-40 Gy/10 fractions (n = 3/20), and 66 Gy/33 fractions (n = 2/20). The median follow-up was 9 months (range, 0.3-29). All pts completed the planned MRgFUS+MB treatments. The only MRgFUS+MB treatment-related toxicity consisted of Grade 1 allergic reaction (mild cough) 30 minutes after the last MB injection. All worst acute toxicities were radiation dermatitis (Grade 3 = 2/20, Grade 2 = 2/20, Grade 1 = 14/20). At 3 months, 75% had partial (n = 6/20) or complete (n = 9/20) response, with a single progression. The LC rate at 1 year was 86%.

CONCLUSION

MRgFUS+MB was a safe and efficient treatment that provided durable responses.

Deep Learning for Automatic Prediction of Lymph Node Station Metastasis in Esophageal Cancer Patients from Contrast-Enhanced CT

PURPOSE/OBJECTIVE(S)

The diagnosis of lymph node (LN) metastasis in computed tomography (CT) is an essential yet challenging task in esophageal cancer staging and treatment planning. Although criteria (e.g., RECIST, morphological/texture features) are proposed to predict LN metastasis, the diagnostic accuracy remains low with sensitivity <50% and specificity <75%, as reported in previous studies. Deep learning (DL) has the potential to address this issue by learning from large-scale labeled data. However, due to the practical surgery procedure in lymph node dissection, it is difficult to pair the metastasis of individual LN reported in the pathology report to the LN instance found in the CT image. Hence, in this study, we first use pathology reports to determine the LNS metastasis, then develop a multiple instance deep learning (MIDL) model to predict lymph node station (LNS) metastasis.

MATERIALS/METHODS

We collected 1200 esophageal cancer patients with preoperative contrast-enhanced CT before surgery. A recently developed automatic mediastinal LNS segmentation model was first applied to segment LNS of 1 to 8 based on the IASLC protocol. For each LNS, the local CT region of interest (ROI) was cropped to generate a station-wise CT patch, where the LNS was labeled as metastatic if at least one metastatic LN was indicated in the pathology report. Using the station-wise CT patch and LNS label, we train a 3D MIDL model, MobileNetV3, to predict LNS metastasis. To better provide the LN position priors in MIDL, LN instances (with a short axis >4mm) were also segmented using an automatic LN detection algorithm and were added to the MIDL model as an auxiliary input. Five-fold cross-validation was conducted to evaluate the MIDL performance.

RESULTS

The MIDL model's performance is summarized in Table 1. The MIDL model incorporating an additional LN instance mask demonstrated a superior overall AUC of 0.7539, surpassing the model without the LN mask input by 2.93%. The specificity was evaluated at a threshold resulting in a recall of 0.7, and the best model outperformed the CT input model in terms of specificity by 2.11%. This highlights the value of including the LN position prior to the MIDL model. Notably, when a threshold was set to result in a specificity of 75%, the best MIDL model demonstrated a significantly higher recall compared to the previously reported clinical diagnostic recall (39.7% vs. 63.21%).

CONCLUSION

We developed a MIDL classification model to predict LNS metastasis using CT scans of 1200 patients. Our findings suggest that the MIDL model can substantially improve LNS metastasis prediction and has the potential to play an essential role in cancer staging, treatment planning, and prognostic analysis.

Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy

PURPOSE/OBJECTIVE(S)

In lung cancer radiation therapy, clinicians must outline the gross tumor volume (GTV) precisely on the planning computed tomography (pCT) for accurate radiation dose delivery. However, due to the limited contrast between tumor and normal tissues in lung parenchyma, accurate delineation of tumor boundaries is difficult leading to large inter-observer variation. In this study, we develop an anatomy-guided lung GTV deep segmentation model using a training cohort of multi-center datasets. The quantitative segmentation performance is evaluated on an independent dataset, where the inter-observer delineation variation is also assessed.

MATERIALS/METHODS

We collected and curated four publicly available lung datasets with GTV annotations (Lung-PET-CT-Dx, LIDC-IDRI, NSCLC-Radiogenomics and RIDER-CT) for deep learning model development. A total of 871 CT scans of patients, who were diagnosed with T1-T4 NSCLC, were available for training after data curation. The GTV annotations of primary tumor were examined and edited by two experienced radiation oncologists following the RTOG 1106 protocol. An anatomy-guided deep learning model was proposed, which consisted two deep networks. The first deep network used CT scan as input and segmented 4 anatomic organs (airway, heart, pulmonary artery and pulmonary vein), while the second deep network took both CT scan and these pre-segmented 4 organs as input and segmented the lung GTV. With the help of anatomic priors from 4 pre-segmented organs, the second deep network could more easily locate the GTV. We used nnUNet as the deep segmentation network. For evaluation, we used NSCLC-Radiomics as the testing dataset, which contains 20 CT scans each annotated by 5 radiation oncologists. The auto-segmented GTV were compared against each of the manual GTV reference. Inter-observer variation was also assessed using the 5 manual GTV references.

RESULTS

The proposed anatomic-guided lung GTV segmentation model achieved a mean Dice score of 82.4% and 95% Hausdorff distance (HD95) of 6.9mm when averaged cross 20 patients and 5 GTV references (Table 1), which outperformed the basic deep GTV segmentation model by markedly reducing 19.4% HD95 error. The performance of proposed model was also comparable to the inter-observer variation (Dice score: 82.4% vs. 81.9%, HD95 6.9 vs. 6.4mm), indicating that our model had similar reproducibility as human observers.

CONCLUSION

We developed and tested an anatomy-guided deep learning model for segmenting GTV in NSCLC patients. The model achieves high quantitative segmentation performance, which is comparable to the human observer variation. It can be potentially used in radiotherapy practice to improve GTV delineation consistency and reduce workloads of radiation oncologists.

Mechanism of Polygonum capitatum intervention in pulmonary fibrosis based on network pharmacology and molecular docking technology: A review

Pulmonary fibrosis (PF) is a serious interstitial disease that includes diffuse collagen deposition of lung tissue. Polygonum capitatum Buch.-Ham. ex D. Don (THL) is a traditional vaccine that has antibacterial and anti-inflammatory effects. In this research, to investigate the mechanism of action of THL in the intervention of pulmonary fibrosis by network pharmacology and molecular docking related research methods, in order to provide a theoretical basis for expanding the scope of THL medication. A total of 49 active ingredients were analyzed and screened in Cephalus cephalusis, including 35 pulmonary fibrosis targets, and 10 key targets such as ALB, EGFR were screened after software analysis. The molecular docking results showed that there were 44 binding energies less than -3 kcal·mol-1 in the 60 docking results, indicating that most proteins had strong binding energies with compounds. The key targets of KEGG enrichment analysis were mainly enriched in 20 core action pathways, such as hemostasis-related pathway, regulation of kinase activity. This study shows that based on network pharmacology, the multicomponent-multitarget-multipathway effect of THL intervention in pulmonary fibrosis is discussed.

Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study

Background

With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden.

Methods

We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation.

Findings

Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5 km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts.

Interpretation

Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission.

Funding

Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).

Co-doping of Ho-Yb ion pairs modulating the up-conversion luminescence properties of fluoride phosphors under 1550 nm excitation

In this study, up-conversion fluoride phosphors NaY1-x-y-m-nMxF4:Er3+y,Ho3+m,Yb3+n (M = Lu3+/Gd3+) were synthesized by a low-temperature combustion method. The optimal ionic ratios in the matrix lattice were also determined by a controlled variable method. It was confirmed that doping a small amount of Ho3+ ions and Yb3+ ions in the Er-doped sample matrix lattice can form a mutual sensitizer and a transient energy capture center to enhance the sample's up-conversion luminescence under excitation at the 1550 nm band, respectively. It was also found that the lanthanide ion introduced can modulate the red-to-green ratio of the up-conversion luminescence of the sample. The phase composition and morphology of phosphors were investigated using X-ray diffraction and scanning electron microscopy. The up-conversion luminescence mechanism of Er-Ho-Yb tri-doped samples excited at the 1550 nm band was also investigated. This work presents a novel approach for improving up-conversion luminescence with high color-purity phosphors for display lighting applications when excited at 1550 nm.

Angiogenic Activity and Mechanism for Bisphenols on Endothelial Cell and Mouse: Evidence of a Structural-Selective Effect

Increased epidemiological evidence indicates the association of bisphenol exposure with human vascular disorders, while the underlying mechanism has not been clarified. Here, we sought to unveil the potential angiogenic effect and the underlying mechanism of bisphenols with different structural features using endothelial cells treated with an environmentally relevant concentration of bisphenols (range: 1 nM to 10 μM) and a C57BL/6 mouse model fed with doses of 0.002, 0.02, 2, and 20 mg/kg BW/day for 5 weeks. Bisphenol A (BPA) and bisphenol S (BPS) at a 1 nM level significantly increased tube formation by 45.1 and 30.2% and induced the microvessel sprouting, while tube length and microvessel sprouting were significantly inhibited by 37.2 and 55.7% after exposure to tetrabromobisphenol S (TBBPS) at 1 μM, respectively. Mechanistically, TBBPA and TBBPS significantly inhibited the interaction between phosphatidylinositol 3-kinase (PI3K) and thyroid receptor (TR), while BPA and BPS favored the interaction between PI3K and estrogen receptor (ER), resulting in abnormal PI3K signaling with consequent distinct angiogenic activity. BPA- and BPS-induced pro-angiogenic effects and TBBPS showed anti-angiogenic effects due to their distinct disruption on the TR/ER-PI3K pathway. Our work provided new evidence and mechanistic insight on the angiogenic activity of bisphenols and expanded the scope of endocrine disruptors with interference in vascular homeostasis.

Observation of high-energy neutrinos from the Galactic plane

The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.

Sensitive electrochemical measurement of nitric oxide released from living cells based on dealloyed PtBi alloy nanoparticles

Nitric oxide (NO), as a vital signaling molecule related to different physiological and pathological processes in living systems, is closely associated with cancer and cardiovascular disease. However, the detection of NO in real-time remains a difficulty. Here, PtBi alloy nanoparticles (NPs) were synthesized, dealloyed, and then fabricated to NP-based electrodes for the electrochemical detection of NO. Transmission electron microscopy (TEM), small-angle X-ray scattering (SAXS), and nitrogen physical adsorption/desorption show that dealloyed PtBi alloy nanoparticles (dPtBi NPs) have a porous nanostructure. Electrochemical impedance spectroscopy and cyclic voltammetry results exhibit that the dPtBi NP electrode possesses unique electrocatalytic features such as low charge transfer resistance and large electrochemically active surface area, which lead to its excellent NO electrochemical sensing performance. Owing to the higher density of catalytical active sites formed PtBi bimetallic interface, the dPtBi NP electrode displays superior electrocatalytic activity toward the oxidation of NO with a peak potential at 0.74 V vs. SCE. The dPtBi NP electrode shows a wide dynamic range (0.09-31.5 μM) and a low detection limit of 1 nM (3σ/k) as well as high sensitivity (130 and 36.5 μA μM^-1 cm^-2). Moreover, the developed dPtBi NP-based electrochemical sensor also exhibited good reproducibility (RSD 5.7%) and repeatability (RSD 3.4%). The electrochemical sensor was successfully used for the sensitive detection of NO produced by live cells. This study indicates a highly effective approach for regulating the composition and nanostructures of metal alloy nanomaterials, which might provide new technical insights for developing high-performance NO-sensitive systems, and have important implications in enabling real-time detection of NO produced by live cells.

[Exploration of clinical pathway-oriented optimal management diagnosis and treatment model for rare diseases]

This study takes Cushing's syndrome, a rare disease, as a model, and adopts the path of "Plan, Do, Check, Action" (PDCA) to explore new methods to optimize the clinical path, can improve the quality and efficiency of diagnosis and treatment of rare diseases. After sorting out the problems existing in the previous diagnosis and treatment mode, our team optimizes the path in various ways and establishes a standard operation procedure (SOP) for the new path. In the evaluation of the optimized mode, 55 patients with Cushing's syndrome were admitted to the Department of Endocrinology, Peking Union Medical College Hospital, including 19 males and 36 females, aged (41.8±14.4) years (6-68 years). The pathway group (28 cases) and the control group (27 cases) were divided according to whether they were included in the new path management at the time of admission, and the effect of path optimization was assessed in terms of time, efficacy, safety and cost. The results showed that compared with the control group, the pathway group had a shorter time of hospitalization in the Department of Endocrinology and critical tests, such as blood cortisol rhythm, low-dose dexamethasone inhibition test, and bilateral inferior petrosal sinus sampling (all P<0.05). There was no significant differences in the decrease of total cortisol after operation, the incidence of postoperative complications, and hospitalization expenses (all P>0.05). The optimized path improves the medical efficiency while ensuring medical quality, safety and no increase in cost. This study proposes PDCA path optimization for complex diseases and establishes SOP process, which provides experience in management optimization for the patient-centered and clinical path-oriented diagnosis and treatment mode of rare diseases.

[The past, present and future of sleep medicine in China]

Sleep is a highly conserved phenomenon in endotherms, and has a universal physiological function across all species. In mammals, sleep can be divided into two stages: rapid eye movement (REM) sleep and non-REM (NREM) sleep, which alternate in a cyclic manner. Humans spend about one-third of their lives asleep. Sufficient sleep is necessary for humans to sustain everyday functioning. Sleep plays an important role in regulating energy metabolism, immune defense, endocrine function, and the consolidation of memory process. With the development of social economy and the change of life style, sleep duration of the residents has gradually decreased and the incidence of sleep disturbances has increased. Sleep disturbances can lead to severe mental disorders, such as depression, anxiety disorders, dementia, and other mental diseases, and may increase the risk of physical diseases, such as chronic inflammation, heart disease, diabetes, hypertension, atherosclerosis and others. Maintaining good sleep is of great significance for developing social productive forces, promoting sustainable development of economic society, and is a necessary condition for carrying out the "Healthy China Strategy". The sleep research in China started in 1950s. After decades of development, researchers have made great progress in the molecular mechanisms of sleep and wakefulness, the pathogenesis of sleep disorders and the development of new therapies. With the advancement of science and technology and the public's attention to sleep, the level of clinical diagnosis and therapy of sleep disorders in China is gradually brought in line with international standards. The publication of diagnosis and treatment guidelines in the field of sleep medicine will promote the standardization of the construction. In the future, it is still necessary to promote the development of sleep medicine in the following aspects: Strengthening the professional training and discipline construction, improving the cooperation of sleep research, promoting the intelligent diagnosis and treatment of sleep disorders, and developing the new intervention strategies. Therefore, this review will comprehensively summarize the origin, current situation, and future expectations of sleep medicine in China, including discipline construction of sleep medicine, the number of sleep project grants, research findings, the status and progress of diagnosis and treatment of sleep disorders, and the development direction of sleep medicine.

A Zn-coordination polymer for the quantitative and selective colorimetric detection of residual tetracycline in aqueous solution and urine

A one-step solvothermal synthesis provides a functional crystalline one-dimensional Zn-coordination polymer (Zn-CP) with excellent stability in aqueous solution over a wide range of temperature and pH. Zn-CP is a rapid, highly sensitive and selective sensor for detecting tetracycline (TC). Quantitative TC detection is based on the ratio of fluorescence intensities I₅₃₀/I₄₂₀, with a limit of detection (LOD) of 5.51 nM in aqueous solution and 47.17 nM in human urine. The characteristics of colorimetric TC sensing by Zn-CP are highly favorable for application because the color of Zn-CP changes in the visible part of the spectrum from blue-purple to yellow-green upon addition of TC. Conversion of these colors into an RGB signal is simply achieved with an app for the smart phone and provides LODs of 8.04 nM and 0.13 μM TC in water and urine, respectively. Our suggested sensing mechanisms assume that the fluorescence intensity of Zn-CP@TC at 530 nm is enhanced by energy transfer of Zn-CP to TC, while the fluorescence of Zn-CP at 420 nm is quenched by photoinduced electron transfer (PET) from TC to the organic ligand in Zn-CP. These fluorescence properties make Zn-CP a convenient, low-cost, rapid and green detection device for monitoring TC under physiological conditions and in aqueous media.

[A region-level contrastive learning-based deep model for glomerular ultrastructure segmentation on electron microscope images]

OBJECTIVE

We propose a novel region- level self-supervised contrastive learning method USRegCon (ultrastructural region contrast) based on the semantic similarity of ultrastructures to improve the performance of the model for glomerular ultrastructure segmentation on electron microscope images.

METHODS

USRegCon used a large amount of unlabeled data for pre- training of the model in 3 steps: (1) The model encoded and decoded the ultrastructural information in the image and adaptively divided the image into multiple regions based on the semantic similarity of the ultrastructures; (2) Based on the divided regions, the first-order grayscale region representations and deep semantic region representations of each region were extracted by region pooling operation; (3) For the first-order grayscale region representations, a grayscale loss function was proposed to minimize the grayscale difference within regions and maximize the difference between regions. For deep semantic region representations, a semantic loss function was introduced to maximize the similarity of positive region pairs and the difference of negative region pairs in the representation space. These two loss functions were jointly used for pre-training of the model.

RESULTS

In the segmentation task for 3 ultrastructures of the glomerular filtration barrier based on the private dataset GlomEM, USRegCon achieved promising segmentation results for basement membrane, endothelial cells, and podocytes, with Dice coefficients of (85.69 ± 0.13)%, (74.59 ± 0.13)%, and (78.57 ± 0.16)%, respectively, demonstrating a good performance of the model superior to many existing image-level, pixel-level, and region-level self-supervised contrastive learning methods and close to the fully- supervised pre-training method based on the large- scale labeled dataset ImageNet.

CONCLUSION

USRegCon facilitates the model to learn beneficial region representations from large amounts of unlabeled data to overcome the scarcity of labeled data and improves the deep model performance for glomerular ultrastructure recognition and boundary segmentation.

[A descriptive analysis of hyperlipidemia in adult twins in China]

Objective: To describe the distribution characteristics of hyperlipidemia in adult twins in the Chinese National Twin Registry (CNTR) and explore the effect of genetic and environmental factors on hyperlipidemia. Methods: Twins recruited from the CNTR in 11 project areas across China were included in the study. A total of 69 130 (34 565 pairs) of adult twins with complete information on hyperlipidemia were selected for analysis. The random effect model was used to characterize the population and regional distribution of hyperlipidemia among twins. The concordance rates of hyperlipidemia were calculated in monozygotic twins (MZ) and dizygotic twins (DZ), respectively, to estimate the heritability. Results: The age of all participants was (34.2±12.4) years. This study's prevalence of hyperlipidemia was 1.3% (895/69 130). Twin pairs who were men, older, living in urban areas, married,had junior college degree or above, overweight, obese, insufficient physical activity, current smokers, ex-smokers, current drinkers, and ex-drinkers had a higher prevalence of hyperlipidemia (P<0.05). In within-pair analysis, the concordance rate of hyperlipidemia was 29.1% (118/405) in MZ and 18.1% (57/315) in DZ, and the difference was statistically significant (P<0.05). Stratified by gender, age, and region, the concordance rate of hyperlipidemia in MZ was still higher than that in DZ. Further, in within-same-sex twin pair analyses, the heritability of hyperlipidemia was 13.04% (95%CI: 2.61%-23.47%) in the northern group and 18.59% (95%CI: 4.43%-32.74%) in the female group, respectively. Conclusions: Adult twins were included in this study and were found to have a lower prevalence of hyperlipidemia than in the general population study, with population and regional differences. Genetic factors influence hyperlipidemia, but the genetic effect may vary with gender and area.

[A descriptive analysis on hypertension in adult twins in China]

Objective: To describe the distribution characteristics of hypertension among adult twins in the Chinese National Twin Registry (CNTR) and to provide clues for exploring the role of genetic and environmental factors on hypertension. Methods: A total of 69 220 (34 610 pairs) of twins aged 18 and above with hypertension information were selected from CNTR registered from 2010 to 2018. Random effect models were used to describe the population and regional distribution of hypertension in twins. To estimate the heritability, the concordance rates of hypertension were calculated and compared between monozygotic twins (MZ) and dizygotic twins (DZ). Results: The age of all participants was (34.1±12.4) years. The overall self-reported prevalence of hypertension was 3.8%(2 610/69 220). Twin pairs who were older, living in urban areas, married, overweight or obese, current smokers or ex-smokers, and current drinkers or abstainers had a higher self-reported prevalence of hypertension (P<0.05). Analysis within the same-sex twin pairs found that the concordance rate of hypertension was 43.2% in MZ and 27.0% in DZ, and the difference was statistically significant (P<0.001). The heritability of hypertension was 22.1% (95%CI: 16.3%- 28.0%). Stratified by gender, age, and region, the concordance rate of hypertension in MZ was still higher than that in DZ. The heritability of hypertension was higher in female participants. Conclusions: There were differences in the distribution of hypertension among twins with different demographic and regional characteristics. It is indicated that genetic factors play a crucial role in hypertension in different genders, ages, and regions, while the magnitude of genetic effects may vary.