Perspective Review of Myeloid Immune Cell Responses and Poststroke Immunosuppression.

Ischemic stroke profoundly influences the peripheral immune system, which responds quickly to brain ischemia and participates in the evolution of poststroke neuroinflammation, while a period of systemic immunosuppression ensues. Poststroke immunosuppression brings harmful consequences, including increased infection rates and escalated death. As the most abundant cell population in the fast-responding innate immune system, myeloid cells including neutrophils and monocytes play an indispensable role in systemic immunosuppression after stroke. The change in myeloid response after stroke can be regulated by circulating DAMPs (damage-associated molecular patterns) and neuromodulatory mechanisms, which contain sympathetic nervous system, hypothalamic-pituitary-adrenal, and parasympathetic nervous system. In this review, we summarize the emerging roles and newly identified mechanisms underlying myeloid cell response in poststroke immunosuppression. Deeper understanding of the above points may pave the way for future development of novel therapeutic strategies to treat poststroke immunosuppression.

Deep learning-based lesion detection and severity grading of small-bowel Crohn's disease ulcers on double-balloon endoscopy images.

BACKGROUND AND AIMS: Double-balloon endoscopy (DBE) is widely used in diagnosing small-bowel Crohn's disease (CD). However, CD misdiagnosis frequently occurs if inexperienced endoscopists cannot accurately detect the lesions. The CD evaluation may also be inaccurate owing to the subjectivity of endoscopists. This study aimed to use artificial intelligence (AI) to accurately detect and objectively assess small-bowel CD for more refined disease management. METHODS: We collected 28,155 small-bowel DBE images from 628 patients from January 2018 to December 2022. Four expert gastroenterologists labeled the images, and at least 2 endoscopists made the final decision with agreement. A state-of-the-art deep learning model, EfficientNet-b5, was trained to detect CD lesions and evaluate CD ulcers. The detection included lesions of ulcer, noninflammatory stenosis, and inflammatory stenosis. Ulcer grading included ulcerated surface, ulcer size, and ulcer depth. A comparison of AI model performance with endoscopists was performed. RESULTS: The EfficientNet-b5 achieved high accuracies of 96.3% (95% confidence interval [CI], 95.7%-96.7%), 95.7% (95% CI, 95.1%-96.2%), and 96.7% (95% CI, 96.2%-97.2%) for the detection of ulcers, noninflammatory stenosis, and inflammatory stenosis, respectively. In ulcer grading, the EfficientNet-b5 exhibited average accuracies of 87.3% (95% CI, 84.6%-89.6%) for grading the ulcerated surface, 87.8% (95% CI, 85.0%-90.2%) for grading the size of ulcers, and 85.2% (95% CI, 83.2%-87.0%) for ulcer depth assessment. CONCLUSIONS: The EfficientNet-b5 achieved high accuracy in detecting CD lesions and grading CD ulcers. The AI model can provide expert-level accuracy and objective evaluation of small-bowel CD to optimize the clinical treatment plans.

The levels and related factors of mental workload among nurses: A systematic review and meta-analysis.

AIM: The aim was to determine the overall levels and related factors of mental workload assessed using the NASA-TLX tool among nurses. BACKGROUND: Mental workload is a key element that affects nursing performance. However, there exists no review regarding mental workload assessed using the NASA-TLX tool, focusing on nurses. DESIGN: A systematic review and meta-analysis. DATA SOURCES: PubMed, MEDLINE, Web of Science, EMBASE, PsycINFO, Scopus, CINAHL, CNKI, CBM, Weipu and WanFang databases were searched from 1 January 1998 to 30 February 2022. REVIEW METHODS: Following the PRISMA statement recommendations, review methods resulted in 31 quantitative studies retained for inclusion which were evaluated with the evaluation criteria for observational studies as recommended by the Agency for Healthcare Research and Quality. The data were pooled and a random-effects meta-analysis conducted. RESULTS: Findings showed the pooled mental workload score was 65.24, and the pooled prevalence of high mental workload was 54%. Subgroup analysis indicated nurses in developing countries and emergency departments experienced higher mental workloads, and the mental workloads of front-line nurses increased significantly during the COVID-19 pandemic. CONCLUSION: These findings highlight that nurses experience high mental workloads as assessed using the NASA-TLX tool and there is an urgent need to explore interventions to decrease their mental workloads.

Psychological capital and organizational citizenship behavior among nurses during the COVID-19 epidemic: mediation of organizational commitment.

BACKGROUND: Nurses' organizational citizenship behavior, a spontaneous "altruistic work behavior", may be affected by psychological capital and organizational commitment, but its mechanism is not clear. The aim of this study was to investigate the characteristics and distribution of psychological capital, organizational commitment and organizational citizenship behavior among nurses during the COVID-19 epidemic, and explore the mediating role of organizational commitment in psychological capital and organizational citizenship behavior. METHODS: A cross-sectional survey was conducted among 746 nurses from 6 designated hospitals for COVID-19 treatment in China. Descriptive statistics, Pearson correlation analysis, and structural equation model were used in this study. RESULTS: Nurses' psychological capital, organizational commitment and organizational citizenship behavior scores were 103.12 ± 15.57, 46.53 ± 7.14 and 101.47 ± 12.14, respectively. Additionally, organizational commitment partially mediates between psychological capital and organizational citizenship behavior. CONCLUSIONS: During the COVID-19 pandemic, nurses' psychological capital, organizational commitment, and organizational citizenship behavior were found to be at an upper-middle level, influenced by various social-demographic factors. Furthermore, the results illustrated that psychological capital can affect organizational citizenship behavior through the mediating role of organizational commitment. Therefore, the findings emphasize the importance of nursing administration to monitor and prioritize the mental health and organizational behavior of nurses during the ongoing COVID-19 crisis. It is crucial to focus on developing and nurturing nurses' psychological capital, strengthening their organizational commitment, and ultimately promoting their organizational citizenship behavior.

[Effect of Pulsating Vacuum Cleaning Sterilizer on the Cleaning Quality of Dental Handpieces].

Objective: To explore the effect of pulsating vacuum cleaning sterilizer on the cleaning quality of dental handpieces. Methods: A total of 390 newly-purchased high-speed dental handpieces were covered in the study. By the random number table method, the handpieces were divided into three groups that were cleaned by different methods-Group A ( n=130), pulsating vacuum cleaning sterilizer, group B ( n=130), automatic thermal cleaning and disinfection machine, and group C ( n=130), manual cleaning. The cleaning quality, internal cavity drying and the length of cleaning time of the three groups were compared. Results: The cleaning quality of group A (100%) was better than those of groups B (89.2%) and C (83.8%) and the length of cleaning time of group A (1.13 h) was shorter than those of group B (1.80 h) and C (2.60 h), all showing significant differences ( P<0.05). In addition, the cleaning quality of group B was better than that of group C and the length of cleaning time of group B was shorter than that of group C, all showing significant differences ( P<0.05). However, there was no significant difference in the internal cavity drying effects between the three groups ( P>0.05). Conclusions: The pulsating vacuum cleaning sterilizer can effectively improve the cleaning quality of dental handpieces and shorten the cleaning time. Hence, it should be extensively applied and promoted in clinic service.

Prevalence and factors of posttraumatic growth among Hubei residents during the COVID-19 pandemic: A cross-sectional study.

The adverse impact of the COVID-19 pandemic on mental health has been widely concerned, but the research on positive psychological factors is insufficient, this study aims to investigate the prevalence and factors of posttraumatic growth (PTG) among residents in the worst-hit areas of China (Hubei Province). We were conducted in three disaster areas with different severity in Hubei Province three months after the outbreak, and the data were from 575 respondents. Instruments included the simplified Chinese version of the Posttraumatic Growth Inventory (C-PTGI) and the public health emergency psychological questionnaire. Nonparametric tests, Spearman correlation analyses, and multiple linear regression equations were used to analyze the data. The results showed that three months after the outbreak of COVID-19, the PTG of Hubei residents was at a low level, and their sense of fear was the most prominent, with a positive detection rate of 82.09%. According to the results of this study, high PTG levels were associated with high levels of fear, married and healthcare providers, while low levels of PTG were associated with serious chronic diseases, males, good economic status, and poor prevention and control measures. Government departments should strengthen social support for residents, carry out necessary stress management training to help them correctly deal with negative emotions and promote their personal growth.

The relationship between organizational commitment and work engagement among clinical nurses in China: A cross-sectional study.

AIM: This study aims to investigate the levels of organizational commitment and work engagement among clinical nurses in tertiary hospitals and explore the relationship between them. BACKGROUND: The nursing literature supports the idea that organizational commitment plays an important role in positively influencing job performance. However, the relationship between organizational commitment and work engagement among clinical nurses remains unclear. METHODS: This was a cross-sectional study. A convenience sample of clinical nurses (n = 621) was selected from five tertiary hospitals in Sichuan Province of China. Survey instruments included a general information questionnaire about organizational commitment and work engagement. Univariate analysis, correlation analyses and linear regression analysis were used to examine the association between organizational commitment and work engagement. RESULTS: The mean scores for organizational commitment and work engagement were 3.85 ± 0.59 and 4.58 ± 1.46, respectively. A moderate degree of positive correlation was found between them. Gender, monthly income and retention commitment were significantly associated with work engagement, and they accounted for 39.0% of the total variance. CONCLUSIONS: Clinical nurses had a moderate level of organizational commitment and a high level of work engagement. Organizational commitment positively influenced work engagement; that is, organizational commitment is a significant determinant of nurses' work engagement. IMPLICATIONS FOR NURSING MANAGEMENT: Hospital organizations should focus on assessing and strengthening nurses' organizational commitment to promote increased work engagement and, ultimately, improved quality of care. This may include, but is not limited to, increasing rest time for nurses, implementing a performance appraisal system and focusing on nurses' psychological state.

Psychological Symptoms and Posttraumatic Growth Among the General Population in Wuhan, China During the COVID-19 Pandemic: A Cross-Sectional Study.

The aim of the current study was to investigate psychological symptoms and post-traumatic growth (PTG) among the general population in Wuhan, China during the coronavirus disease 2019 (COVID-19) pandemic. An online survey was conducted using convenience sampling. Participants were invited to fill out this questionnaire, which included information on sociodemographic characteristics and other survey objectives. The Psychological Questionnaire for Emergent Events of Public Health (PQEEPH) and the Chinese version of the Posttraumatic Growth Inventory (PTGI) were used. The prevalence of depression, neurasthenia, fear, obsessive-anxiety, and hypochondriasis among 311 participants were 61.1%, 69.8%, 97.8%, 57.2%, and 45%, respectively. Results indicated that a substantial proportion of the general population may have experienced psychological symptoms as well as PTG, due to the COVID-19 pandemic. Findings demonstrate the importance of developing targeted psychological interventions for those at risk for mental health symptoms. [Journal of Psychosocial Nursing and Mental Health Services, 60(4), 39-46.].

The levels, prevalence and related factors of compassion fatigue among oncology nurses: a systematic review and meta-analysis.

BACKGROUND: Compassion fatigue is described as the phenomenon of exhaustion and dysfunction in healthcare workers resulting from prolonged exposure to work-related stress and compassion stress. Oncology nurses are at high risk for compassion fatigue. AIMS: Our study aims to estimate the levels, prevalence and related factors of compassion fatigue dimension in oncology nurses. DESIGN: Systematic review and meta-analysis. METHOD: Ten electronic databases were conducted in the systematic review and meta-analysis. Time frame of the searches is from inception up to 31 January 2020. The research team independently conducted study selection, quality assessments, data extractions and analysis of all included studies. The means, standard deviations and prevalence of three dimensions of compassion fatigue were pooled using random-effects meta-analysis. The PRISMA guideline was used to report the systematic review and meta-analysis. PROSPERO registration number: CRD42020205521. RESULTS: The systematic review included 21 studies, involving 6533 oncology nurses across 6 different countries. In our studies, the pooled mean scores of compassion satisfaction (CS), burnout (BO) and secondary traumatic stress (STS) were 35.47 (95% CI: 33.54-37.41), 24.94 (95% CI: 23.47-26.41) and 24.48 (95% CI: 23.36-25.60), respectively; the pooled prevalence of "low" rates of CS, "high" rates of BO and STS were 20% (CI 13%-28%), 22% (CI 18%-26%) and 22% (CI 17%-28%), respectively; furthermore, geographical regions (Asia) significantly affect the prevalence of compassion fatigue among oncology nurses. The compassion fatigue variables considered were demographic (age, marital status, education background, health condition and gender), work-related (job satisfaction, income satisfaction, years of working experience, professional title, position and work environment) and other variables (social support, coping strategy, self-compassion, professional cognition and psychological training). CONCLUSION: Oncology nurses were at "moderate" level of compassion satisfaction, burnout and secondary traumatic stress, and 22% of oncology nurses suffered from "high" risk of compassion fatigue. Hospital administrators should develop interventions to address compassion fatigue phenomenon, and enhance the mental health of oncology nurses and nursing care results. RELEVANCE TO CLINICAL PRACTICE: Oncology unit warrants special attention, and oncology nurses are at high risk for compassion fatigue. However, the reported prevalence rates and oncology nurses with different characteristics vary considerably. The review provides a preliminary framework for nursing administrators to develop interventions to address compassion fatigue phenomenon, and enhance the psychological health of oncology nurses.

Serum miRNAs are potential biomarkers for the detection of disc degeneration, among which miR-26a-5p suppresses Smad1 to regulate disc homeostasis.

Disc degeneration is a common clinical condition in which damaged discs cause chronic pain; however, a laboratory diagnosis method for its detection is not available. As circulating miRNAs have potential as biomarkers, their application in disc degeneration has not been explored. Here, we prepared serum miRNAs from a mouse disc degeneration model and performed miRNA-Seq and quantitative PCR to characterize disc degeneration-associated miRNAs. We identified three miRNAs, including miR-26a-5p, miR-122-5p and miR-215-5p, undergoing perturbation during the pathogenesis of disc degeneration. Specifically, the levels of miR-26a-5p in the serum demonstrated steady increases in the model of disc degeneration, compared with those in the pre-injury samples of younger age or compared with normal controls of the same age but without disc degeneration, whereas the miRNAs miR-122-5p and miR-215-5p exhibited lower expression in post-injury samples than in their counterparts without the surgery. Moreover, we found that miR-26a-5p targets Smad1 expression, and Smad1 negatively regulates Vegfa expression in disc cells, and thus, miR-26a-5p promotes disc degeneration. In summary, we established a method that consistently profiles circulating miRNAs and identified multiple miRNAs as promising biomarkers for disc degeneration, among which miR-26a-5p enhances VEGF expression during disc degeneration through targeting Smad1 signalling.

Velvet antler polypeptide partially rescue facet joint osteoarthritis-like phenotype in adult ß-catenin conditional activation mice.

BACKGROUND: Wnt/ß-catenin signaling pathway is closely related to osteoarthritis. In our preliminary study, ß-catenin conditional activation (cAct) mice that specifically over-express ß-catenin gene in cartilage chondrocyte exhibits osteoarthritis-like phenotype in the lumbar disc and knee joint. Therefore, we used the mice to model FJ-OA and test the potential curative effect of Velvet Antler Polypeptide (VAP) on this mice model. METHODS: We tested the effect of VAP on ß-catenin conditional activation mice, and used Cre negative littermates as controls. Micro-CT, histology and histomorphometry analysis were performed to evaluate the curative effect of VAP on mice facet joint-like phenotype. Expression of ß-catenin and collagen II was detected by immunohistochemistry (IHC) and western-blot., MMP13, ADAMTS4 and ADAMTS5 was detected by immunofluorescence (IF). RT-PCR analysis was preformed to detect mRNA expression of cartilage degrading enzymes, such as MMP13, ADAMTS4 and ADAMTS5. RESULTS: Results of micro-CT (µCT) analysis showed that VAP could partially reverse lumbar disc osteophyte formation observed in ß-catenin(ex3)Col2ER mice. Histology data revealed VAP partially improved facet joint cartilage tissue invades. Histomorphometry analysis showed an increase in total cartilage area after VAP treatment. IHC show that VAP reduced ß-catenin protein levels and moderately up-regulated collagen II protein levels. RT-PCR and IF data showed that VAP down-regulated the expression of extracellular matrix synthesis (ECM) degradation enzymes MMP13, ADAMTS4 and ADAMTS5. CONCLUSION: Taken together, VAP may modulate ECM by inhibits MMP13, ADAMTS4 and ADAMTS5 via Wnt /ß-catenin signaling pathway. Velvet Antler Polypeptide may be a potential medicine for FJ-OA.

Packet error rate analysis of digital pulse interval modulation in intersatellite optical communication systems with diversified wavefront deformation.

Diversified wavefront deformation is an inevitable phenomenon in intersatellite optical communication systems, which will decrease system performance. In this paper, we investigate the description of wavefront deformation and its influence on the packet error rate (PER) of digital pulse interval modulation (DPIM). With the wavelet method, the diversified wavefront deformation can be described by wavelet parameters: coefficient, dilation, and shift factors, where the coefficient factor represents the depth, dilation factor represents the area, and shift factor is for location. Based on this, the relationship between PER and wavelet parameters is analyzed from a theoretical viewpoint. Numerical results illustrate the validity of theoretical analysis: PER increases with the depth and area and decreases if location gets farther from the center of the optical antenna. In addition to describing diversified deformation, the advantage of the wavelet method over Zernike polynomials in computational complexity is shown via numerical example. This work provides a feasible method for the description along with influence analysis of diversified wavefront deformation from a practical viewpoint and will be helpful for designing optical systems.

Burden of intracerebral haemorrhage in Europe: forecasting incidence and mortality between 2019 and 2050.

Background: Anticipating the burden of intracerebral haemorrhage is crucial for proactive management and building resilience against future health challenges. Prior forecasts are based on population demography and to a lesser extent epidemiological trends. This study aims to utilise selected modifiable risk factors and socio-demographic indicators to forecast the incidence and mortality of intracerebral haemorrhage in Europe between 2019 and 2050. Methods: Three intracerebral haemorrhage risk factors identified in the Global Burden of Diseases, Injuries, and Risk Factors study (GBD 2019)-high systolic blood pressure, high fasting plasma glucose, and high body mass index-were utilised to predict the risk-attributable fractions between 2019 and 2050. Disease burden not attributable to these risk factors was then forecasted using time series models (autoregressive integrated moving average [ARIMA]), incorporating the Socio-demographic Index (SDI) as an external predictor. The optimal parameters of ARIMA models were selected for each age-sex-country group based on the Akaike Information Criterion (AIC). Different health scenarios were constructed by extending the past 85th and 15th percentiles of annualised rates of change in risk factors and SDI across all location-years, stratified by age and sex groups. A decomposition analysis was performed to assess the relative contributions of population size, age composition, and intracerebral haemorrhage risk on the projected changes. Findings: Compared with observed figures in 2019, our analysis predicts an increase in the burden of intracerebral haemorrhage in Europe in 2050, with a marginal rise of 0.6% (95% uncertainty interval [UI], -7.4% to 9.6%) in incident cases and an 8.9% (-2.8% to 23.6%) increase in mortality, reaching 141.2 (120.6-166.5) thousand and 144.2 (122.9-172.2) thousand respectively. These projections may fluctuate depending on trajectories of the risk factors and SDI; worsened trends could result in increases of 16.7% (8.7%-25.3%) in incidence and 31.2% (17.7%-48%) in mortality, while better trajectories may lead to a 10% (16.4%-2.3%) decrease in intracerebral haemorrhage cases with stabilised mortality. Individuals aged ≥80 years are expected to contribute significantly to the burden, comprising 62.7% of the cases in 2050, up from 40% in 2019, and 72.5% of deaths, up from 50.5%. Country-wide variations were noted in the projected changes, with decreases in the standardised rates across all nations but varying crude rates. The largest relative reductions in counts for both incidence and mortality are expected in Latvia, Bulgaria, and Hungary-ranging from -38.2% to -32.4% and -37.3% to -30.2% respectively. In contrast, the greatest increases for both measures were forecasted in Ireland (45.7% and 74.4%), Luxembourg (45% and 70.7%), and Cyprus (44.5% and 74.2%). The modelled increase in the burden of intracerebral haemorrhage could largely be attributed to population ageing. Interpretation: This study provides a comprehensive forecast of intracerebral haemorrhage in Europe until 2050, presenting different trajectories. The potential increase in the number of people experiencing and dying from intracerebral haemorrhage could have profound implications for both caregiving responsibilities and associated costs. However, forecasts were divergent between different scenarios and among EU countries, signalling the pivotal role of public health initiatives in steering the trajectories. Funding: The European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 754517. The National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research (NIHR202339).

Development and Validation of a Deep-Learning Network for Detecting Congenital Heart Disease from Multi-View Multi-Modal Transthoracic Echocardiograms.

Early detection and treatment of congenital heart disease (CHD) can significantly improve the prognosis of children. However, inexperienced sonographers often face difficulties in recognizing CHD through transthoracic echocardiogram (TTE) images. In this study, 2-dimensional (2D) and Doppler TTEs of children collected from 2 clinical groups from Beijing Children's Hospital between 2018 and 2022 were analyzed, including views of apical 4 chamber, subxiphoid long-axis view of 2 atria, parasternal long-axis view of the left ventricle, parasternal short-axis view of aorta, and suprasternal long-axis view. A deep learning (DL) framework was developed to identify cardiac views, integrate information from various views and modalities, visualize the high-risk region, and predict the probability of the subject being normal or having an atrial septal defect (ASD) or a ventricular septaldefect (VSD). A total of 1,932 children (1,255 healthy controls, 292 ASDs, and 385 VSDs) were collected from 2 clinical groups. For view classification, the DL model reached a mean [SD] accuracy of 0.989 [0.001]. For CHD screening, the model using both 2D and Doppler TTEs with 5 views achieved a mean [SD] area under the receiver operating characteristic curve (AUC) of 0.996 [0.000] and an accuracy of 0.994 [0.002] for within-center evaluation while reaching a mean [SD] AUC of 0.990 [0.003] and an accuracy of 0.993 [0.001] for cross-center test set. For the classification of healthy, ASD, and VSD, the model reached the mean [SD] accuracy of 0.991 [0.002] and 0.986 [0.001] for within- and cross-center evaluation, respectively. The DL models aggregating TTEs with more modalities and scanning views attained superior performance to approximate that of experienced sonographers. The incorporation of multiple views and modalities of TTEs in the model enables accurate identification of children with CHD in a noninvasive manner, suggesting the potential to enhance CHD detection performance and simplify the screening process.

Global Burden of Ischemic Heart Disease from 2022 to 2050: Projections of Incidence, Prevalence, Deaths, and Disability-Adjusted Life Years.

AIMS: Ischemic heart disease (IHD) has been a significant public health issue worldwide. This study aims to predict the global burden of IHD in a timely and comprehensive manner. METHODS AND RESULTS: Incidence, prevalence, deaths, and disability-adjusted life years (DALYs) for IHD from 1990 to 2021 were derived from the Global Burden of Disease 2021 database and three models (linear, exponential, and Poisson regression) were used to estimate their trends over time at the global, regional, and national levels by age, sex, and country groups, with the gross domestic product per capita was applied to adjust the model. The model results revealed that the global burden of IHD is expected to increase continuously by 2050. By 2050, global IHD incidence, prevalence, deaths, and DALYs are projected to reach 67.3 million, 510 million, 16 million, and 302 million, respectively, which represents an increase of 116%, 106%, 80%, and 62% from 2021. Moreover, the results showed that regions with lower socio-demographic index (SDI) bore a greater burden of IHD than those with higher SDI, with men having a higher burden of IHD than women. People over 70 years old account for a major part of the burden of IHD, and premature death of IHD is also becoming more serious. CONCLUSION: The global burden of IHD will increase further by 2050, potentially due to population aging and economic disparities. Hence, it is necessary to strengthen the prevention of IHD and formulate targeted strategies according to different SDI regions and special populations.

Malignancy-associated ischemic stroke: Implications for diagnostic and therapeutic workup.

BACKGROUND: Patients with malignancies have an increased risk of suffering ischemic stroke via several mechanisms such as coagulation dysfunction and other malignancy-related effects as well as iatrogenic causes. Moreover, stroke can be the first sign of an occult malignancy, termed as malignancy-associated ischemic stroke (MAS). Therefore, timely diagnostic assessment and targeted management of this complex clinical situation are critical. FINDINGS: Patients with both stroke and malignancy have atypical ages, risk factors, and often exhibit malignancy-related symptoms and multiple lesions on neuroimaging. New biomarkers such as eicosapentaenoic acid and blood mRNA profiles may help in distinguishing MAS from other strokes. In terms of treatment, malignancy should not be considered a contraindication, given comparable rates of recanalization and complications between stroke patients with or without malignancies. CONCLUSION: In this review, we summarize the latest developments in diagnosing and managing MAS, especially stroke with occult malignancies, and provide new recommendations from recently emerged clinical evidence for diagnostic and therapeutic workup strategies.

Ferroptosis: the vulnerability within a cancer monster.

Treatment-resistant cancer, such as neuroendocrine prostate cancer (NEPC), is a lethal disease with limited therapeutic options. RB1 is a tumor suppressor gene that is lost in a majority of NEPC tumors. In this issue of the JCI, Wang and colleagues examined how RB1 loss may sensitize cancer cells to ferroptosis inducers through elevation of ACSL4, a key enzyme that promotes lipid peroxidation and triggers ferroptosis. We discuss a high potential of RB1-deficient cells to undergo ferroptosis due to the elevation of ACSL4. This is normally kept in check by abundant expression of GPX4, an antioxidant enzyme, in cancer cells. This balance, however, is tilted by GPX4 inhibitors, leading to massive ferroptosis. We highlight possible therapeutic strategies that exploit this inherent vulnerability for targeting RB1-deficient, treatment-resistant cancer.

Source-free domain adaptive segmentation with class-balanced complementary self-training.

Unsupervised domain adaptation (UDA) plays a crucial role in transferring knowledge gained from a labeled source domain to effectively apply it in an unlabeled and diverse target domain. While UDA commonly involves training on data from both domains, accessing labeled data from the source domain is frequently constrained, citing concerns related to patient data privacy or intellectual property. The source-free UDA (SFUDA) can be promising to sidestep this difficulty. However, without the source domain supervision, the SFUDA methods can easily fall into the dilemma of "winner takes all", in which the majority category can dominate the deep segmentor, and the minority categories are largely ignored. In addition, the over-confident pseudo-label noise in self-training-based UDA is a long-lasting problem. To sidestep these difficulties, we propose a novel class-balanced complementary self-training (CBCOST) framework for SFUDA segmentation. Specifically, we jointly optimize the pseudo-label-based self-training with two mutually reinforced components. The first class-wise balanced pseudo-label training (CBT) explicitly exploits the fine-grained class-wise confidence to select the class-wise balanced pseudo-labeled pixels with the adaptive within-class thresholds. Second, to alleviate the pseudo-labeled noise, we propose a complementary self-training (COST) to exclude the classes that do not belong to, with a heuristic complementary label selection scheme. We evaluated our CBCOST framework on both 2D and 3D cross-modality cardiac anatomical segmentation tasks and brain tumor segmentation tasks. Our experimental results showed that our CBCOST performs better than existing SFUDA methods and yields similar performance, compared with UDA methods with the source data.

Neutrophil-derived cathelicidin promotes cerebral angiogenesis after ischemic stroke.

Neutrophils play critical roles in the evolving of brain injuries following ischemic stroke. However, how they impact the brain repair in the late phase after stroke remain uncertain. Using a prospective clinical stroke patient cohort, we found significantly increased cathelicidin antimicrobial peptide (CAMP) in the peripheral blood of stroke patients compared to that of healthy controls. While in the mouse stroke model, CAMP was present in the peripheral blood, brain ischemic core and significantly increased at day 1, 3, 7, 14 after middle cerebral artery occlusion (MCAO). CAMP-/- mice exhibited significantly increased infarct volume, exacerbated neurological outcome, reduced cerebral endothelial cell proliferation and vascular density at 7 and 14 days after MCAO. Using bEND3 cells subjected to oxygen-glucose deprivation (OGD), we found significantly increased angiogenesis-related gene expression with the treatment of recombinant CAMP peptide (rCAMP) after reoxygenation. Intracerebroventricular injection (ICV) of AZD-5069, the antagonist of CAMP receptor CXCR2, or knockdown of CXCR2 by shCXCR2 recombinant adeno-associated virus (rAAV) impeded angiogenesis and neurological recovery after MCAO. Administration of rCAMP promoted endothelial proliferation and angiogenesis and attenuated neurological deficits 14 days after MCAO. In conclusion, neutrophil derived CAMP represents an important mediator that could promote post-stroke angiogenesis and neurological recovery in the late phase after stroke.