A Waterproof Flexible Paper-Based Thermoelectric Generator for Humidity and Underwater Environments

A thermoelectric generator (TEG) is one of the important energy harvesting sources for wearable electronic devices, which converts waste heat into electrical energy without any external stimuli, such as light or mechanical motion. However, the poor flexibility of traditional TEGs (e.g., Si-based TE devices) causes the limitations in practical applications. Flexible paper substrates are becoming increasingly attractive in wearable electronic technology owing to their usability, environmental friendliness (disposable, biodegradable, and renewable materials), and foldability. The high water-absorbing quality of paper restricts its scope of application due to water failure. Therefore, we propose a high-performance flexible waterproof paper-based thermoelectric generator (WPTEG). A modification method that infiltrates TE materials into cellulose paper through vacuum filtration is used to prepare the TE modules. By connecting the TE-modified paper with Al tape, as well as a superhydrophobic layer encapsulation, the WPTEG is fabricated. The WPTEG with three P-N modules can generate an output voltage of up to 235 mV at a temperature difference of 50 K, which can provide power to portable electronic devices such as diodes, clocks, and calculators in hot water. With the waterproof property, the WPTEG paves the way for achieving multi-scenario applications in humid environments on human skin.

The mental health of Australians bereaved during the first two years of the COVID-19 pandemic: a latent class analysis

BACKGROUND

The COVID-19 pandemic disrupted many areas of life, including culturally accepted practices at end-of-life care, funeral rites, and access to social, community, and professional support. This survey investigated the mental health outcomes of Australians bereaved during this time to determine how these factors might have impacted bereavement outcomes.

METHODS

An online survey indexing pandemic and bereavement experiences, levels of grief, depression, anxiety, and health, work, and social impairment. Latent class analysis (LCA) was used to identify groups of individuals who shared similar symptom patterns. Multinomial regressions identified pandemic-related, loss-related, and sociodemographic correlates of class membership.

RESULTS

1911 Australian adults completed the survey. The LCA identified four classes: low symptoms (46.8%), grief (17.3%), depression/anxiety (17.7%), and grief/depression/anxiety (18.2%). The latter group reported the highest levels of health, work, and social impairment. The death of a child or partner and an inability to care for the deceased due to COVID-19 public health measures were correlated with grief symptoms (with or without depression and anxiety). Preparedness for the person's death and levels of pandemic-related loneliness and social isolation differentiated all four classes. Unemployment was associated with depression/anxiety (with or without grief).

CONCLUSIONS

COVID-19 had profound impacts for the way we lived and died, with effects that are likely to ricochet through society into the foreseeable future. These lessons learned must inform policymakers and healthcare professionals to improve bereavement care and ensure preparedness during and following future predicted pandemics to prevent negative impacts.

Human RNA-binding protein HNRNPD interacts with and regulates the repair of deoxyribouridine in DNA

Deoxyribouridine (dU) is an abnormal nucleoside in DNA and plays vital roles in multiple biological and physiological processes. Here, we conducted a mass spectrometry-based screen for dU-binding proteins and found that the heterogeneous nuclear ribonucleoprotein D (HNRNPD) could preferentially bind to dU-containing DNA. We also discovered that HNRNPD engages in the 5-Fluorouracil (5FU)-induced DNA damage response and can modulate the repair of dU in DNA in vitro and in human cells. Moreover, using a shuttle vector- and next-generation sequencing-based method, we unveiled the crucial role of HNRNPD in promoting the replicative bypass of dU in human cells. Taken together, these findings suggested that HNRNPD is a novel dU-bearing DNA-binding protein capable of regulating the removal of dU in DNA, and provided new insights into the molecular mechanisms of dU-associated diseases.

RUNX3 inhibits KSHV lytic replication by binding to the viral genome and repressing transcription

Kaposi's sarcoma-associated herpesvirus (KSHV) belongs to the gamma herpesvirus family, which can cause human malignancies including Kaposi sarcoma, primary effusion lymphoma, and multicentric Castleman's diseases. KSHV typically maintains a persistent latent infection within the host. However, after exposure to intracellular or extracellular stimuli, KSHV lytic replication can be reactivated. The reactivation process of KSHV triggers the innate immune response to limit viral replication. Here, we found that the transcriptional regulator RUNX3 is transcriptionally upregulated by the NF-κB signaling pathway in KSHV-infected SLK cells and B cells during KSHV reactivation. Notably, knockdown of RUNX3 significantly promotes viral lytic replication as well as the gene transcription of KSHV. Consistent with this finding, overexpression of RUNX3 impairs viral lytic replication. Mechanistically, RUNX3 binds to the KSHV genome and limits viral replication through transcriptional repression, which is related to its DNA- and ATP-binding ability. However, KSHV has also evolved corresponding strategies to antagonize this inhibition by using the viral protein RTA to target RUNX3 for ubiquitination and proteasomal degradation. Altogether, our study suggests that RUNX3, a novel host-restriction factor of KSHV that represses the transcription of viral genes, may serve as a potential target to restrict KSHV transmission and disease development.IMPORTANCEThe reactivation of Kaposi's sarcoma-associated herpesvirus (KSHV) from latent infection to lytic replication is important for persistent viral infection and tumorigenicity. However, reactivation is a complex event, and the regulatory mechanisms of this process are not fully elucidated. Our study revealed that the host RUNX3 is upregulated by the NF-κB signaling pathway during KSHV reactivation, which can repress the transcription of KSHV genes. At the late stage of lytic replication, KSHV utilizes a mechanism involving RTA to degrade RUNX3, thus evading host inhibition. This finding helps elucidate the regulatory mechanism of the KSHV life cycle and may provide new clues for the development of therapeutic strategies for KSHV-associated diseases.

[Automated cephalometric landmark identification and location based on convolutional neural network]

Objective: To develop an automated landmark location system applicable to the case of landmark missing. Methods: Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to January 2021 in the Department of Orthodontics, Capital Medical University School of Stomatology, and met the inclusion criteria were collected. Five postgraduate orthodontic students were the annotators to manually locate 61 possible landmarks in 481 lateral cephalograms. Two assistant professors in the department as reviewers performed calibration. Two professors as arbitrators, made final decision. Data sets were established (341 were used as training set, 40 as validation set, and 100 as test set). In this paper, an automatic landmarks identification and location model based on convolutional neural networks (CNN), CephaNET, was developed. The model was trained by feeding the original image into the feature extraction module and convolutional pose machine (CPM) module to locate landmarks with high accuracy using deep supervision. Training set was enhanced to 1 684 images by histogram equalization, cropping, and adjustment of brightness. The model was trained to compare the Gaussian heat maps output from the network with the set threshold to identify landmark missing cases. Test set of 100 lateral cephalograms was used to test the accuracy of the model. The evaluation criteria used were success detection rate of missing landmark, mean radial error (MRE) and success detection rate (SDR) in the range of 2.0, 2.5, 3.0, 3.5 and 4.0 mm. Results: The model identified and located 61 commonly used landmarks in 0.13 seconds on average. It had an average accuracy of 93.5% in identifying missing landmarks. The MRE of our testing set was (1.19±0.91) mm. SDR of 2.0, 2.5, 3.0, 3.5 and 4.0 mm were 85.4%, 90.2%, 93.5%, 95.4%, 97.0% respectively. Conclusions: The model proposed in this paper could adapt to the absence of landmark in lateral cephalograms and locate 61 commonly used landmarks with high accuracy to meet the requirements of different cephalometric analysis methods.

MetaLnc9 facilitates osteogenesis of human bone marrow mesenchymal stem cells by activating the AKT pathway

AIM OF THE STUDY

To investigate the role of MetaLnc9 in the osteogenesis of human bone marrow mesenchymal stem cells (hBMSCs).

MATERIALS AND METHODS

We used lentiviruses to knockdown or overexpress MetaLnc9 in hBMSCs. qRT-PCR was employed to determine the mRNA levels of osteogenic-related genes in transfected cells. ALP staining and activity assay, ARS staining and quantification were used to identify the degree of osteogenic differentiation. Ectopic bone formation was conducted to examine the osteogenesis of transfected cells in vivo. AKT pathway activator SC-79 and inhibitor LY294002 were used to validate the relationship between MetaLnc9 and AKT signaling pathway.

RESULTS

The expression of MetaLnc9 was significantly upregulated in the osteogenic differentiation of hBMSCs. MetaLnc9 knockdown inhibited the osteogenesis of hBMSCs, whereas overexpression of it promoted the osteogenic differentiation both in vitro and in vivo. Taking a deeper insight, we found that MetaLnc9 enhanced the osteogenic differentiation by activating AKT signaling. The inhibitor of AKT signaling LY294002 could reverse the positive effect on osteogenesis brought by MetaLnc9 overexpression, whereas the activator of AKT signaling SC-79 could reverse the negative effect caused by MetaLnc9 knockdown.

CONCLUSION

Our works uncovered a vital role of MetaLnc9 in osteogenesis via regulating the AKT signaling pathway. [Figure: see text].

SIRT1 slows the progression of lupus nephritis by regulating the NLRP3 inflammasome through ROS/TRPM2/Ca2+ channel

Systemic lupus erythematosus (SLE) is a chronic multisystem inflammatory disease associated with autoantibody formation. Lupus nephritis (LN) is one of the most severe organ manifestations of SLE. The inflammatory response is a key factor in kidney injury, and the NLRP3 inflammasome is frequently associated with the pathogenesis of LN. Sirtuin 1 (SIRT1), a nicotinamide adenine dinucleotide (NAD +)-dependent histone deacetylase, is a promising therapeutic target for preventing renal injury. However, the mechanism of SIRT1 in LN remains unclear. Here, we aimed to investigate the mechanism by which SIRT inhibits the NLRP3 inflammasome to slow the progression of LN. We detected the expression of SIRT1 and the infiltration of macrophages in MRL/lpr mice; the results showed that the expression of SIRT1 was decreased, and the symptoms of lupus nephritis were relieved after the use of resveratrol, which upregulated SIRT1. In vitro studies showed that after lipopolysaccharide (LPS) stimulation, SIRT1 expression decreased, and the NLRP3 inflammasome was activated. Upregulation of SIRT1 inhibits NLRP3 inflammasome activation and assembly by interfering with two signalling pathways. First, SIRT1 affects NF-κB expression, transcription, and inflammatory cytokine expression. Second, SIRT1 modulates calcium influx induced by transient receptor potential channel M2 (TRPM2), which could be partly due to the inhibition of reactive oxygen species (ROS) production. Our findings suggest that upregulated SIRT1 inhibits the NLRP3 inflammasome to slow the progression of lupus nephritis by regulating NF-κB and ROS/TRPM2/Ca2+ channels. This study reveals a new anti-inflammatory mechanism of SIRT1, suggesting that SIRT1 may be a potential therapeutic target for the prevention of LN.

Treatment Tolerance and Toxicity in Elderly Oropharyngeal Cancer Patients and Implication on Outcomes

PURPOSE/OBJECTIVE(S)

To investigate the tolerance level and toxicity for standard of care treatment for oropharyngeal cancer (OP) in elderly patients and their impact on outcomes.

MATERIALS/METHODS

Using our in-house head and neck cancer database, we looked for non-metastatic OP cases that received definitive treatment between 1/2009-6/2020. All patients received either definitive radiation therapy (RT) +/- concomitant systemic therapy (ST), or surgery followed by adjuvant RT or RT-ST. For the elderly (age at diagnosis ≥65 years) and young (<65 years) patients, we compared treatment package time (TPT) (time from surgery to RT conclusion) for adjuvant RT, total RT duration and unplanned RT interruptions. ST details and dose/protocol modifications were also compared. We evaluated worst grade of pain and mucositis, hospitalization for non-hydration causes and febrile neutropenia (FN) during RT. Feeding tube (FT) use and weight loss were compared. The independent effect of these indicators on locoregional (LRFS), distant (DRFS) recurrence free and overall (OS) survival was assessed using multivariate analyses (MVA).

RESULTS

A cohort of 326 patients was included: 36% elderly (n = 118) and 64% young (n = 208), with no differences in AJCC stage distribution (8th), treatment received and HPV status (HPV+ve: 73% vs 74.6%; p = 0.86). In 23.6 % who received adjuvant RT, median TPT was 86 (range 72-128) and 81 (65-137) days for elderly vs young (p = 0.27); whereas in the definitive RT cases 76.4%, total RT duration was 49 days for both age groups. Overall, prescribed RT course was not completed in 4% and unplanned RT interruptions occurred in 22.8% and both were non-significant between age groups. Among the 261 patients that received ST, elderly utilized more cetuximab (26 vs 12%; p = 0.007). For those who received cisplatin, 20% of elderly had cumulative dose <200 mg/m2 compared to 6% among the younger age group (p = 0.006); and cisplatin was changed to carboplatin or cetuximab in 18% vs 8% (p = 0.019). Delayed/cancelled cycles and dose reductions were similar. There were more hospitalizations (47% vs 27%; p<0.001) and a trend for more FN (9% vs 3%; p = 0.09) with older age, while worst pain and mucositis was similar. FTs were used more in elderly patients (64% vs 50%; p = 0.02), for a median of 97 vs 64 days (p = 0.31); of which 19.5% vs 11% (p = 0.28) were inserted before RT start. However, % weight loss was non-significant. On MVA, longer RT duration, FT use and hospitalizations predicted worse LRFS and DRFS; and they were prognostic for OS in addition to TPT >90 days (p<0.05 for all). Nevertheless, elderly vs young had non-significant 3-year LRFS (91% vs 90% and 67% vs 69%), DRFS (86% vs 90% and 79% vs 81%) & OS (85% vs 81% and 39% vs 52%) for HPV+ve and HPV-ve respectively (p>0.05).

CONCLUSION

Elderly patients with OP need more multi-disciplinary supportive care when receiving RT and concurrent ST. However, survival outcomes are equivalent to younger patients. Ongoing studies should enroll more elderly candidates and stratify endpoints with age.

Sexual Orientation and Gender Identity (SOGI) Data Collection: Opportunities to Advance Best Clinical Practices for LGBTQ+ Patients in Radiation Oncology

PURPOSE/OBJECTIVE(S)

A long-standing barrier to progress against health disparities is the lack of data regarding cancer risks, prevalence, treatment, and outcomes for sexual and gender minority (SGM) patients. Sexual orientation and gender identity (SOGI) data are not routinely collected by individual oncologists, cancer centers, or most non-federal hospital systems. Alarmingly high proportions of SGM patients report discrimination in healthcare or avoid routine care due to perceived lack of acceptance in the healthcare system. For these and other reasons, healthcare institutions must adopt practices that promote an inclusive environment for all patients including those self-identified from SGM groups. One strategy to achieve this aim is through SOGI data collection. The purpose of this study was to pilot new procedures and training for SOGI data collection, the aims of this project were to standardize the collection of SOGI data for all new patients referred to the Division of Radiation Oncology; promote clinical staff awareness of SGM health disparities and strategies for fostering an inclusive hospital environment; and to provide SGM patients and caregivers educational resources and support systems tailored to their needs.

MATERIALS/METHODS

We designed a Quality Improvement program for collecting SOGI data, which was approved by our institution's QIAB. Patient access specialists (PAS) were trained to collect SOGI data from newly registered patients and enter the data into the electronic health record. Radiation Oncology staff completed surveys before and after SOGI training to estimate its impact on the provision of patient care. A Fisher's exact test was utilized to evaluate associations between training and provider-reported outcomes.

RESULTS

Within a 3-week period starting in January 2023, two 1-hour interactive training sessions were offered to twenty-five PAS. Three 1-hour training sessions were offered to twenty-seven Radiation Oncology clinical staff. (1) Confidence for incorporating SOGI classifiers around patients improved from before training (52%, 13/25) to after training (100%, 17/17) among medical providers surveyed (odds ratio (OR) 32, 95% confidence interval (CI) 0.70-1493, p = 0.005). Use of SOGI data in clinical decision making increased from before training (9/25, 36%) to after training (100%, 17/17) among medical providers (OR 60.79, 95% CI 3.271-1130, p<0.0001). (2) A clinical pathway for SGM patients was developed to facilitate referral to our institution's SGM patient support group and distribution of patient education materials focused on sexual health.

CONCLUSION

Establishing standardized SOGI data collection can facilitate the provision of tailored resources and care that meets the needs of patients and staff in a large comprehensive cancer center. Specialized training for staff developed through this initiative helps foster an inclusive and welcoming environment that promotes the integration, visibility, and advancement of SGM cancer care at our institution.

S1P/S1PR1 axis promotes macrophage M1 polarization through NLRP3 inflammasome activation in Lupus nephritis

Lupus nephritis (LN) is a common complication of systemic lupus erythematosus (SLE) as well as the leading cause of mortality in patients. Previous studies revealed that S1P level is elevated in plasma samples of SLE patients and murine lupus models. FTY720, targeting S1P receptors, exhibited therapeutic effects in improving the nephritis symptoms of lupus mouse models. However, few studies have discussed the potential relevance of S1P/S1PR to the pathogenesis of LN. Macrophages have been shown to be an important causative agent of renal inflammation, while the pro-inflammatory M1-type promotes kidney injury and inflammation during LN. Importantly, macrophages express various S1P receptors, and how they respond to S1P in the setting of LN remains unclear. Therefore, we examined the level of S1P in the lupus MRL/lpr mice and explored the ensuing interaction of macrophages and S1P. We found that S1P level was elevated in the MRL/lpr mice with a subsequent enhancement of the S1PR1 expression, and blocking S1PR1 by FTY720, the nephritis symptoms of MRL/lpr mice were improved. Mechanistically, we demonstrated that elevated S1P level increase the M1-type macrophage accumulation. And the in-vitro studies proved that S1P/S1PR1 was involved in the promotion of macrophage polarization towards M1 type through activation of NLRP3 inflammasome. These findings confer a novel role to macrophage S1PR1 and provide a new perspective for targeting S1P during LN.

Enabling early detection of knee osteoarthritis using diffusion-relaxation correlation spectrum imaging

AIM

To present a technique that enables detection of early stage OA of the knee using diffusion-relaxation correlation spectrum imaging (DR-CSI).

MATERIALS AND METHODS

Fifty-five early osteoarthritis patients (OA, Kellgren-Lawrence [KL] score 1 to 2; mean age, 56.4 years) and 49 healthy volunteers (mean age, 56.7 years) were underwent magnetic resonance imaging (MRI) with T2-mapping and DR-CSI techniques. Maps of mean apparent diffusion coefficient (ADC), T2 relaxation time and volume fraction Vi for DR-CSI compartment i (A, B, C, D) sensitivity, specificity, and positive and negative likelihood ratio (PLR, NLR) were assessed to determine the diagnostic accuracy for detection of early-stage degeneration of knee articular cartilage. The structural abnormalities of articular cartilage were evaluated using modified Whole-Organ MR Imaging Scores (WORMS).

RESULTS

All intra- and interobserver agreements for DR-CSI compartment volume fractions and modified WORMS of cartilage were excellent. Early OA versus the controls had higher V_C, lower V_A and V_B (p<0.001), but comparable V_D (p>0.05). V_A, V_B and V_C had a moderate association with WORMS. No significant correlation was identified between V_D and WORMS. V_C had better ability than V_A,V_B, V_D, T2 and ADC to discriminate early OA patients from healthy controls (area under the curve, 0.898). Sensitivity, specificity, PLR, and NLR of V_C with a cut-off value of 29.9% were 81.8% (95% confidence interval [CI], 69.1-90.9%), 95.9% (86-99.5%), 20.05% (5.13-78.34%), and 0.19% (0.11-0.33%).

CONCLUSIONS

DR-CSI compartment volume fractions may be sensitive indicators for detecting early-stage degeneration in knee articular cartilage.

[Automated diagnostic classification with lateral cephalograms based on deep learning network model]

Objective: To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. Methods: A total of 2 894 lateral cephalograms were collected in Department of Orthodontics, Capital Medical University School of Stomatology from January 2015 to December 2021 to construct a data set, including 1 351 males and 1 543 females with a mean age of (26.4± 7.4) years. Firstly, 2 orthodontists (with 5 and 8 years of orthodontic experience, respectively) performed manual annotation and calculated measurement for primary classification, and then 2 senior orthodontists (with more than 20 years of orthodontic experience) verified the 8 diagnostic classifications including skeletal and dental indices. The data were randomly divided into training, validation, and test sets in the ratio of 7∶2∶1. The open source DenseNet121 was used to construct the model. The performance of the model was evaluated by classification accuracy, precision rate, sensitivity, specificity and area under the curve (AUC). Visualization of model regions of interest through class activation heatmaps. Results: The automatic classification model of lateral cephalograms was successfully established. It took 0.012 s on average to make 8 diagnoses on a lateral cephalogram. The accuracy of 5 classifications was 80%-90%, including sagittal and vertical skeletal facial pattern, mandibular growth, inclination of upper incisors, and protrusion of lower incisors. The acuracy rate of 3 classifications was 70%-80%, including maxillary growth, inclination of lower incisors and protrusion of upper incisors. The average AUC of each classification was ≥0.90. The class activation heat map of successfully classified lateral cephalograms showed that the AI model activation regions were distributed in the relevant structural regions. Conclusions: In this study, an automatic classification model for lateral cephalograms was established based on the DenseNet121 to achieve rapid classification of eight commonly used clinical diagnostic items.

[Research on multi-class orthodontic image recognition system based on deep learning network model]

Objective: To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. Methods: A total of 35 000 clinical orthodontic images were collected in the Department of Orthodontics, Capital Medical University School of Stomatology, from October to November 2020 and June to July 2021. The images were from 490 orthodontic patients with a male-to-female ratio of 49∶51 and the age range of 4 to 45 years. After data cleaning based on inclusion and exclusion criteria, the final image dataset included 17 453 face images (frontal, smiling, 90° right, 90° left, 45° right, and 45° left), 8 026 intraoral images [frontal occlusion, right occlusion, left occlusion, upper occlusal view (original and flipped), lower occlusal view (original and flipped) and coverage of occlusal relationship], 4 115 X-ray images [lateral skull X-ray from the left side, lateral skull X-ray from the right side, frontal skull X-ray, cone-beam CT (CBCT), and wrist bone X-ray] and 684 other non-orthodontic images. A labeling team composed of orthodontic doctoral students, associate professors, and professors used image labeling tools to classify the orthodontic images into 20 categories, including 6 face image categories, 8 intraoral image categories, 5 X-ray image categories, and other images. The data for each label were randomly divided into training, validation, and testing sets in an 8∶1∶1 ratio using the random function in the Python programming language. The improved SqueezeNet deep learning model was used for training, and 13 000 natural images from the ImageNet open-source dataset were used as additional non-orthodontic images for algorithm optimization of anomaly data processing. A multi-classification orthodontic image recognition system based on deep learning models was constructed. The accuracy of the orthodontic image classification was evaluated using precision, recall, F1 score, and confusion matrix based on the prediction results of the test set. The reliability of the model's image classification judgment logic was verified using the gradient-weighted class activation mapping (Grad-CAM) method to generate heat maps. Results: After data cleaning and labeling, a total of 30 278 orthodontic images were included in the dataset. The test set classification results showed that the precision, recall, and F1 scores of most classification labels were 100%, with only 5 misclassified images out of 3 047, resulting in a system accuracy of 99.84%(3 042/3 047). The precision of anomaly data processing was 100% (10 500/10 500). The heat map showed that the judgment basis of the SqueezeNet deep learning model in the image classification process was basically consistent with that of humans. Conclusions: This study developed a multi-classification orthodontic image recognition system for automatic classification of 20 types of orthodontic images based on the improved SqueezeNet deep learning model. The system exhibitted good accuracy in orthodontic image classification.

Human Mitochondrial Protein HSPD1 Binds to and Regulates the Repair of Deoxyinosine in DNA

The generation of deoxyinosine (dI) in DNA is one of the most important sources of genetic mutations, which may lead to cancer and other human diseases. A further understanding of the biological consequences of dI necessitates the identification and functional characterizations of dI-binding proteins. Herein, we employed a mass spectrometry-based proteomics approach to detect the cellular proteins that may sense the presence of dI in DNA. Our results demonstrated that human mitochondrial heat shock protein 60 (HSPD1) can interact with dI-bearing DNA. We further demonstrated the involvement of HSPD1 in the sodium nitrite-induced DNA damage response and in the modulation of dI levels in vitro and in human cells. Together, these findings revealed HSPD1 as a novel dI-binding protein that may play an important role in the mitochondrial DNA damage control in human cells.

The effect of microRNA-663b in the inhibition of interleukin-1-induced nucleus pulposus cell apoptosis and inflammatory response

The aim of this study was to explore the role and pathological mechanism of microRNA-663b in interleukin-1beta (IL-1β)-induced inflammation and apoptosis of nucleus pulposus cells. First, the best concentration and time to construct the nucleus pulposus cell inflammation model was screen out. Overexpression or inhibition of miR-663b expression was performed by adding microRNA-663b mimic or microRNA-663b inhibitor. 293T cells were transfected according to experimental requirements. The luciferase activity of each group was detected to analyze the targeted regulation of microRNA-663b on interleukin-1 receptor (IL1R1). Compared with the mimic negative control (NC) group, the expression of inflammatory factors in the microRNA-663b overexpression group was inhibited (P<0.05), and the expression of type 2 collagen and polysaccharide protein increased (P<0.05), and the apoptosis of nucleus pulposus cells was inhibited (P<0.01), and the number of TUNEL-positive cells decreased significantly (P<0.01), and the microRNA and protein expression of IL1R1, the ratio of P-P65/P65 and phospho-nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (P-IκBα)/nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IκBα) protein expression were significantly decreased (P<0.05). The expression of inflammatory factors in the miR-663b inhibitor group was significantly higher than that in the inhibitor NC group (P<0.01), and the expression of type 2 collagen and polysaccharide protein was significantly decreased (P<0.01), and the number of apoptosis cells and TUNEL staining positive cells increased (p<0.01). The expression of IL1R1 gene and protein was significantly increased (P<0.01). The ratio of P-P65/P65 and P-IκBα/IκBα protein expression increased (P<0.05). IL1R1 is a downstream target gene of microRNA-663b. MicroRNA-663b may down-regulate the expression of IL1R1 at the transcriptional level by targeting IL1R1, inhibit the inflammatory response of nucleus pulposus cells, and slow down the degeneration of nucleus pulposus cells.

The effect of microRNA-663b in the inhibition of interleukin-1-induced nucleus pulposus cell apoptosis and inflammatory response

The aim of this study was to explore the role and pathological mechanism of microRNA-663b in interleukin-1beta (IL-1β)-induced inflammation and apoptosis of nucleus pulposus cells. First, the best concentration and time to construct the nucleus pulposus cell inflammation model was screen out. Overexpression or inhibition of miR-663b expression was performed by adding microRNA-663b mimic or microRNA-663b inhibitor. 293T cells were transfected according to experimental requirements. The luciferase activity of each group was detected to analyze the targeted regulation of microRNA-663b on interleukin-1 receptor (IL1R1). Compared with the mimic negative control (NC) group, the expression of inflammatory factors in the microRNA-663b overexpression group was inhibited (P<0.05), and the expression of type 2 collagen and polysaccharide protein increased (P<0.05), and the apoptosis of nucleus pulposus cells was inhibited (P<0.01), and the number of TUNEL-positive cells decreased significantly (P<0.01), and the microRNA and protein expression of IL1R1, the ratio of P-P65/P65 and phospho-nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (P-IκBα)/nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IκBα) protein expression were significantly decreased (P<0.05). The expression of inflammatory factors in the miR-663b inhibitor group was significantly higher than that in the inhibitor NC group (P<0.01), and the expression of type 2 collagen and polysaccharide protein was significantly decreased (P<0.01), and the number of apoptosis cells and TUNEL staining positive cells increased (p<0.01). The expression of IL1R1 gene and protein was significantly increased (P<0.01). The ratio of P-P65/P65 and P-IκBα/IκBα protein expression increased (P<0.05). IL1R1 is a downstream target gene of microRNA-663b. MicroRNA-663b may down-regulate the expression of IL1R1 at the transcriptional level by targeting IL1R1, inhibit the inflammatory response of nucleus pulposus cells, and slow down the degeneration of nucleus pulposus cells.

P10.09.B Retroelement expression in glioma tumors exhibits subtype specific patterns

Background

There are ~3 million transposable elements in the human genome constituting about 42% of all basepairs. Retroelements (REs) are ~90% of the transposable elements present in the human genome. Active REs are considered highly mutagenic and have been implicated in multiple steps of cancer development and progression, as well as in neurologic diseases. RE activity has functional effects on the genome, including the maintenance of centromere and telomere integrity, and deleterious gene expression. Previous studies have shown that certain families of RE (HERVK, L1, Alu) are expressed in gliomas, however, their specific role as arbitrators of oncogenesis or promoters of the innate anti-tumor immune response remains uncertain. Moreover, it has been shown that a soluble form of PD-L1 (sPD-L1) that blocks its inhibitory activity is produced by exaptation of an intronic endogenous retroelement (LINE-2A) in the gene encoding PD-L1, highlighting the importance of REs as potential therapeutic targets. In this analysis we aim to identify the unique patterns of RE expression across major subtypes of glioma.

Material and Methods

We conducted a differential expression analysis of 49 RE families using RNA-seq data measured in glioma tumors from The Cancer Genome Atlas (TCGA). RE counts were produced using the software REDiscoverTE. Pairwise comparisons between glioma subtypes (defined by WHO2021) were done using in 625 tumor samples adjusting for age, sex and race.

Results

10 of the 49 considered RE families exhibited significantly different (false discovery rate, FDR, &lt;0.05) expression in at least one glioma subtype. Alu(Fold change, FC=1.5), RNA(FC=11.3), PiggyBac(FC=1.6), rRNA(FC=5.23) and Dong-R4(FC=1.8) were overexpressed in IDH-wildtype glioblastoma while Gypsy(FC=0.4) and CRP1(FC=0.26) were decreased in expression. scRNA (FC=2.7) were overexpressed in IDH-mutant oligodendroglioma compared to glioblastoma while Dong-R4 (FC = 0.53) showed decreased expression. LTR (FC=2.02) and tRNA-Deu (FC=1.46), showed increased expression in IDH-wildtype diffuse astrocytomas compared to IDH-mutant, 1p/19q-codeleted oligodendrogliomas while Gypsy (FC =0.41) showed decreased expression.

Conclusion

We have shown that expression of certain RE families within gliomas have subtype-specific patterns. While it is well established that RE expression is dysregulated in cancer, our analysis is the first at exploring a wide range of retroelements in the context of glioma by subtype. Given the important role of REs in transcriptional control, genomic instability, chromosomal rearrangements, and oncogenic activation, the identification of individual families and specific REs in glioma holds an intrinsic value to potential biomarkers and immunotherapy targets.

Automatic 3-Dimensional Cephalometric Landmarking via Deep Learning

The increasing use of 3-dimensional (3D) imaging by orthodontists and maxillofacial surgeons to assess complex dentofacial deformities and plan orthognathic surgeries implies a critical need for 3D cephalometric analysis. Although promising methods were suggested to localize 3D landmarks automatically, concerns about robustness and generalizability restrain their clinical use. Consequently, highly trained operators remain needed to perform manual landmarking. In this retrospective diagnostic study, we aimed to train and evaluate a deep learning (DL) pipeline based on SpatialConfiguration-Net for automatic localization of 3D cephalometric landmarks on computed tomography (CT) scans. A retrospective sample of consecutive presurgical CT scans was randomly distributed between a training/validation set (n = 160) and a test set (n = 38). The reference data consisted of 33 landmarks, manually localized once by 1 operator(n = 178) or twice by 3 operators (n = 20, test set only). After inference on the test set, 1 CT scan showed "very low" confidence level predictions; we excluded it from the overall analysis but still assessed and discussed the corresponding results. The model performance was evaluated by comparing the predictions with the reference data; the outcome set included localization accuracy, cephalometric measurements, and comparison to manual landmarking reproducibility. On the hold-out test set, the mean localization error was 1.0 ± 1.3 mm, while success detection rates for 2.0, 2.5, and 3.0 mm were 90.4%, 93.6%, and 95.4%, respectively. Mean errors were -0.3 ± 1.3° and -0.1 ± 0.7 mm for angular and linear measurements, respectively. When compared to manual reproducibility, the measurements were within the Bland-Altman 95% limits of agreement for 91.9% and 71.8% of skeletal and dentoalveolar variables, respectively. To conclude, while our DL method still requires improvement, it provided highly accurate 3D landmark localization on a challenging test set, with a reliability for skeletal evaluation on par with what clinicians obtain.

Role of sphingosine-1-phosphate mediated signalling in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a highly prevalent autoimmune disease characterized by the malfunction of the immune system and the persistent presence of an inflammatory environment. Multiple organs can be affected during SLE, leading to heterogeneous manifestations, which eventually result in the death of patients. Due to the lack of understanding regarding the pathogenesis of SLE, the currently available treatments remain suboptimal. Sphingosine-1-phosphate (S1P) is a central bioactive lipid of sphingolipid metabolism, which serves a pivotal role in regulating numerous physiological and pathological processes. As a well-recognized regulator of lymphocyte trafficking, S1P has been shown to be closely associated with autoimmune diseases, including SLE. Importantly, S1P levels have been found to be elevated in patients with SLE. In murine models of lupus, the increased levels of S1P also contribute to disease activity and organ impairment. Moreover, data from several studies also support the hypothesis that S1P receptors and its producer-sphingosine kinases (SPHK) may serve as the potential targets for the treatment of SLE and its co-morbidities. Given the significant success that intervening with S1P signaling has achieved in treating multiple sclerosis, further exploration of its role in SLE is necessary. Therefore, the aim of the present review is to summarize the recent advances in understanding the potential mechanism by which S1P influences SLE, with a primary focus on its role in immune regulation and inflammatory responses.

A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke

Remote monitoring of physical activity using bodyworn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data were recorded from 10 hemi paretic patients while they carried out a sequence of 11 activities of daily living (Identification tasks), and 10 activities used to evaluate misclassification errors (non-Identification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the non-Identification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of 4 ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0 %, and a mean specificity of 99.7 % for the identification tasks, and a mean misclassification error of < 10% for the non-Identification tasks. The findings support the feasibility of a hybrid sEMG and ACC wearable sensor system for automatic recognition of motor tasks used to assess functional independence in patients with stroke.

The p70S6K/PI3K/MAPK feedback loop releases the inhibition effect of high-dose rapamycin on rat mesangial cell proliferation

Glomerular mesangial cell (MC) proliferation is one of the causative factors of glomerular diseases and one of their prominent pathological features. Rapamycin can inhibit MC proliferation and slow the progression to chronic renal fibrosis. The present study was designed to observe the role of rapamycin in MC proliferation and to explore the mechanism by which rapamycin acts on Akt and MAPK/ERK1/2 pathways in mesangial cells. MTT assay and flow cytometry were used to evaluate the proliferation and the cell cycle phase of glomerular mesangial cells respectively. The mRNA expression level of p70S6K was detected by RT-qPCR. Western blotting was performed to determine p70S6K, PI3K/Akt, and PI3K/MAPK protein expression. We found that rapamycin could reduce mesangial cell proliferation and arrest the cell cycle in the G1 phase, however the inhibition effect of 1000 nmol/L rapamycin was not higher than that in the 100 nmol/L group. The results of western blotting showed that 1000 nmol/L rapamycin more significantly inhibited the phosphorylation of p70S6K than 100 nmol/L, suggesting there should be another signaling pathway that activates the proliferation of MCs. Moreover, our results revealed that 1000 nmol/L rapamycin led to Raf1-MEK1/2-ERK pathway activation through a p70S6K-PI3K-mediated feedback loop in MCs. This study demonstrated that high-dose rapamycin leads to ERK1/2 activation through a p70S6K/PI3K/MAPK feedback loop in rat MCs, thus reducing the inhibitory effect of rapamycin on MC proliferation.

Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences

AIM

To accelerate the acquisition of high-resolution magnetic resonance imaging (MRI) by using the three-dimensional (3D) matrix sequence with compressed sensing and to compare it with conventional two-dimensional (2D) proton-density (PD) and fast spin-echo (FSE) sequences.

MATERIALS AND METHODS

3D matrix, 2D FSE, and PD sequences were acquired from 68 participants using 3 T magnetic resonance imaging (MRI). Two radiologists scored image quality independently on a four-point scale. The structural similarity index (SSIM), and signal- (SNRs) and contrast-to-noise ratios (CNRs) of different anatomical structures of the knee were assessed and compared between sequences using Wilcoxon signed-rank tests and Cohen's kappa.

RESULTS

The median acquisition time reduction was 44.5%. There was a substantial to perfect agreement for the rating between the 3D matrix FSE and 2D FSE or PD sequences when evaluating cartilage, subchondral bone, and ligaments (κ=0.783-872, p>0.05). The mean SSIM values between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences was 0.994 and 0.971, respectively, which are acceptable. No significant differences were found in SNR between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences, even though the SNR appeared to be higher on routine 2D sequences. The CNR of subchondral bone-meniscus, subchondral bone-joint fluid, and meniscus-joint fluid did not differentiate significantly between the 3D matrix sequence and routine 2D sequences.

CONCLUSIONS

3D matrix reduced the acquisition time in routine clinical knee MRI without the loss in image quality, SNR, and CNR.

Differences in the clinical characteristics and long-term outcome of peripartum tako-tsubo cardiomyopathy and peripartum cardiomyopathy

Background

Some peripartum-associated cardiomyopathy patients present similarly to those of tako-tsubo cardiomyopathy (TCM), little is known about the clinical course of peripartum TCM.

Purpose

To know clinicial characteristics and outcomes of peripartum TCM, in comparison with peripartum cardiomyopathy (PPCM)

Methods and results

Of 31 pregnancy-associated cardiomyopathy patients in a tertiary hospital, 10 cases of peripartum TCM and 21 cases of PPCM were found. Maternal near-missed death was significantly more common in the peripartum TCM group than in the PPCM group (100.0% vs. 76.2%, p=0.030). Complete recovery was observed with all peripartum TCM cases, while 23.8% of the PPCM cases had residual left ventricle (LV) dysfunction. LV ejection fraction greater than 30% on the initial echocardiogram independently predicted early echocardiographic recovery of left ventricular systolic function (odds ratio 331.33, 95% confidence interval 3.87–28402.60, p=0.011). There was no difference between the two groups in terms of the rate of adverse clinical events at 3 years of follow-up (PPCM group: 26.3% [5/19] vs. TCM group: 33.3% [3/9], p=0.750).

Conclusions

One-third of pregnancy-associated cardiomyopathy patients had peripartum TCM. With contemporary supportive care, both PPCM and peripartum TCM patients had a low mortality rate and excellent long-term outcomes.

Kaplan-Meier survival curves for death,

Funding Acknowledgement

Type of funding source: None

Detection and quantification of Aflatoxin B1 in corn and corn-grown soils in the district of Anuradhapura, Sri Lanka

Aflatoxin B1 contamination adversely affects human health by impairing long-term physical and cognitive development. Several crops have been associated with aflatoxin B1 contamination and corn is one of them. In the Anuradhapura district of the North Central Province of Sri Lanka, corn is one of the main agricultural produce. Due to poor farming practices in this area, it is possible that aflatoxin B1 is somehow transported from soil to the corn ears. This study was carried out to detect and quantify aflatoxin B1 in corn and corn-grown soils in Anuradhapura. Corn (n = 60) and corn-grown soil (n = 60) samples were randomly collected from 20 minor-scale corn-grown fields with three random replicates. Each sample was prepared for the measurement of aflatoxin B1 levels using the Enzyme-Linked Immunosorbent Assay (ELISA). Though 20 ppb is considered as the poisonous or deleterious level for corn consumption, there were toxin contaminations of up to 60–70 ppb in the corn kernel, while majority of soil had 350–400 ppb of aflatoxin B1 levels. Fifteen corn samples had exceeded the acceptable level while 22 samples were free of aflatoxin B1 and 23 samples were within the acceptable level. The results showed that the presence of aflatoxin B1 in corn is not habitually distributed throughout Anuradhapura district and it increased with the soil aflatoxin B1 concentration. It appears that there is a relationship between corn kernel and corn-grown soil aflatoxin B1 levels.