Thirdly, we can implement hassle-free delivery through rapid manufacturing protocols and off-the-shelf products. Just as the Model T set a benchmark for car manufacturing over 100 years ago, idecabtagene vicleucel and ciltacabtagene autoleucel have now set the starting point for BCMA CAR-T therapy with their approvals. As with any emerging technology, whether automotive or cellular, the best in innovation and optimization is yet to come.Autologous chimeric antigen receptor T-cell (CAR-T) therapies targeting B-cell maturation antigen (BCMA) have revolutionized the field of multiple myeloma in the same way that the Ford Model T revolutionized the original CAR world a century ago. However, we are only beginning to understand how to improve the efficacy and usability of these cellular therapies. In this review, we explore three automotive analogies for innovation with BCMA CAR-T therapies: stronger engines, better mileage, and hassle-free delivery. Firstly, we can build stronger engines in terms of BCMA targeting: improved antigen binding, tools to modulate antigen density, and armoring to better reach the antigen itself. Secondly, we can improve “mileage” in terms of response durability through  Although automobiles were available as early as 1893, the advent of the Model T in 1908 revolutionized the world through innovative and scalable manufacturing processes . Similaractivity . Not untactivity . Of the stronger engines, referring to more potent BCMA targeting (2); better mileage, referring to longer duration of responses; and (3) hassle-free delivery, referring to reduced ‘brain-to-vein’ times between CAR-T consultation and infusion. While still investigational, these strategies collectively promise to dramatically improve the efficacy and practicality of BCMA CAR-T therapy in multiple myeloma.That being said, the need for automotive improvement in the year 1908 was just as pronounced as the need for BCMA CAR-T improvement today. Median PFS in the KarMMa trial of ide-cel was only 8.8 months, while Kaplan-Meier curves from CARTITUDE-1 continue to lack a plateau , 6. SlotThe development of second-generation CARs with co-stimulatory domains to better mimic native T-cell receptor (TCR) function was a seminal step forward for the field of adoptive cellular therapy. Many strategies are under development to continue improving “under the hood” CAR signaling once the receptor binds its target. For example, third-generation CARs contain more than one co-stimulatory domain with the goal of more potently activating T cells , 10. SimCilta-cel, formerly developed in China as LCAR-B38M and in the United States as JNJ-4528, is the most prominent example of alternative BCMA targeting. The second-generation CAR in cilta-cel contains two separate BCMA-binding fragments of heavy-chain-only antibodies (VHH) –14. The Translational research suggests that CAR density and antigen binding affinity influence the functionality of BCMA CAR-T cells in unexpected ways. While one might suspect that more CARs per individual T cell would correspond to more cancer cell death, higher CAR expression may actually be associated with increased T-cell exhaustion and decreased CAR-T cell infiltration into the bone marrow . In the Modulation of target antigen density – namely, membrane-bound BCMA on myeloma cells – also warrants further investigation as well. Gamma secretase is used by plasma cells to shed BCMA from their surfaces, and pre-clinical work suggests that tumor exposure to gamma secretase inhibitors (GSI) can enhance the anti-tumor efficacy of CAR-T cells –26. In aBecause BCMA loss at a genetic level renders tumor cells resistant both to BCMA CAR-T therapy and to the effects of GSIs , 30, sevAs noted in in vivo and in vitro studies  in vivo approaches focused on the modulation of the immune system.A lower bound of the Model T’s fuel economy estimates that drivers in the early 20r gallon . Similarex vivo category, one well-studied strategy is to decrease the immunogenicity of CAR constructs to prevent native B cells from producing antidrug antibodies (ADA) against the CAR-T cells themselves. In the KarMMa trial of ide-cel, 65% of treated patients developed ADAs within 12 months of infusion. Of 28 patients who received a second therapeutic ide-cel infusion on this protocol, responses were observed in 50% of patients without ADAs versus 0% in the presence of ADAs  and CT103A (n = 71) respectively, ADAs have been reported in fewer than 5% of patients  with CARs predicts shorter responses to CD19-directed CAR-T therapy  may improve BCMA CAR-T cell efficacy as well , suboptimal pharmacokinetic fludarabine concentrations may play an important role in relapse  lenalidomide is a well-established tool to prolong responses , it is un = 5), responses to checkpoint inhibition were limited in terms of depth and duration . In addition to evaluations of efficacy, these studies will be important to quantify the risk of immune-related adverse events attributable to PD-1 blockade in this setting – for example, autoimmune colitis or dermatitis – coupled with the theoretical risk of rebound CAR-T immune-related toxicities such as CRS and ICANS.Given the complexity of reasons by which relapse occurs after BCMA CAR-T therapy, however, post-CAR-T checkpoint inhibition may still be beneficial for certain subsets of patients. The timing of PD-1 blockade after CAR-T therapy may also be important in terms of the degree to which T-cell exhaustion is reversed . As suchIn recent years, many electric car manufacturers have set up online car-purchasing portals and automatic vehicle delivery services to minimize the hassles inherent to visiting in-person dealerships and arranging payment financing . These sin vivo CAR-T expansion in patients post-infusion rather than depending on a sufficient number of cells to be cultured ex vivo pre-infusion. PHE885 is a BCMA CAR-T therapy made using a proprietary “T-Charge” platform that, in addition to reducing manufacturing time to 2 days or less, has been shown to preserve T-cell self-renewal and maturation capabilities -compliant production facilities for active homegrown CAR-T research protocols or have acquired automated CAR-T manufacturing devices with this goal in mind , 108. MoFor centers with this infrastructure in place, though, homegrown CAR-T therapies are quite promising. As a specific example in multiple myeloma, ARI0002h is a European second-generation lentiviral BCMA-directed CAR-T therapy. Recently presented data from a Phase 1 study of ARI0002h demonstrate a 100% manufacturing success rate, a median manufacturing time of 11 days, and a median PFS that has not yet been reached with 16 months of follow-up . Most paex vivo manufacturing for each treated patient. These cells could undergo most quality control testing ahead of time and be stored at myeloma treatment centers themselves, hence the moniker that they could be taken “off the shelf” of a freezer and given directly to patients. T-cell apheresis products produced from healthy donors are free of disease and have not been exposed to multiple lines of chemotherapy. In contrast, both myeloma as well as its treatments can compromise the effector function of T-cells that serve as the source of autologous CAR-T products  while the CD52 gene is disrupted to allow for lymphodepletion of native T cells with an anti-CD52 antibody similar to alemtuzumab . In updaOther investigational allogeneic BCMA CAR-T therapies include PBCAR269A, in which proprietary ARCUS gene editing is used to simultaneously knock out the native TCR and ‘knock in’ the anti-BCMA CAR . A PhaseOne of the many quotes attributed to Henry Ford is a quip that he reportedly made during an interview about the Model T: “If I had asked people what they wanted, they would have said faster horses.” . SimilarAs this review demonstrates, however, BCMA CAR-T therapy still has considerable room for improvement. Strategies to make these therapies more potent in terms of BCMA targeting, more consequential in terms of response durability, and more straightforward in terms of brain-to-vein times all warrant further investigation. Given that prolonged exposure to chemotherapy and the myeloma microenvironment may impair T-cell fitness, sequencing BCMA CAR-T therapy earlier in treatment paradigms may increase not only the size of the eligible patient population but also the efficacy of the T-cells being transduced , 124. AnWith all these approaches under active investigation, is the perfect BCMA CAR-T therapy for multiple myeloma within reach? Not yet. As summarized in Like any automobile, our review has two main blind spots in terms of the broader care of patients with MM. Firstly, given our focus on CAR T-cells, we have not discussed the applicability of these strategies to BCMA-targeted bispecific antibody (bsAb) therapies. The evidence base for bsAb therapies in multiple myeloma has been reviewed elsewhere, and the BCMA-targeting bsAb teclistamab has recently gained regulatory approval in Europe and the United States –146. Whibefore BCMA-directed therapies because of evidence that emerges to suggest better and more durable responses. Such a paradigm change, if it does occur some day, will of course require years’ if not decades’ worth of robust evidence from clinical trials of different approaches to therapy sequencing.Our second blind spot is our focus on BCMA, which is unlikely to remain the only target for CAR T therapy in myeloma. We have already discussed a number of other potential antigens in the context of concurrent dual antigen targeting alongside BCMA , 37–42. In conclusion, while BCMA CAR-T therapies have clearly revolutionized the treatment of multiple myeloma, they are far from perfect in their current iterations. The dozens of strategies discussed in this review to improve the efficacy of these therapies can be grouped into three categories: more potent BCMA targeting, longer durations of responses, and reduced brain-to-vein times. Not all such strategies will reach the finish line, of course. As mentioned in this review, once-promising BCMA CAR-T therapies that have been shelved by their manufacturers include (at least four) candidates with initially promising rationales: AUTO2, bb21217, orva-cel, and P-BCMA-101. That being said, we hope to see many more candidate therapies succeed in coming years to make clinical responses to BCMA CAR-T therapy deeper, more durable, and more practical. While the Ford Model T and subsequent automotive innovations have allowed us to traverse any road we please, these innovations in CAR-T design will allow us to focus on a singular road of paramount importance: namely, the road toward curing multiple myeloma.All authors contributed to the article and approved the submitted version.RB: Honoraria: Clinical Care Options; Honoraria: i3 Health; Honoraria: Curio Science; Consultancy: Sanofi Pasteur; Consultancy: Guidepoint Global; Consultancy; Janssen; Consultancy; Genentech/Roche. SL: Consultancy; Abbvie: Consultancy, Research Funding; Nektar: Research Funding; Cellectar: Consultancy; Bristol Myers Squibb: Research Funding; Janssen: Consultancy, Research Funding. AC: Harpoon: Research Funding; Secura Bio: Consultancy; Sanofi Aventis: Consultancy, Research Funding; GSK: Consultancy; Abbvie: Consultancy, Research Funding; Nektar: Research Funding; Cellectar: Consultancy; Bristol Myers Squibb: Research Funding; Janssen: Consultancy, Research Funding.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS).In total, 242 patients with STS  who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models.Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models.The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS. Soft tissue sarcomas (STS) are rare malignant neoplasms having unpredictable clinical and pathologic behaviors . ApproxiThe most common appearance of LMs of STSs is as a pulmonary nodule. However, chest computed tomography (CT) cannot effectively differentiate metastatic lung nodules from non-metastatic ones, and positron emission tomography (PET)-CT scan supplies few extra clinical benefits because of its high false-negative rate for lung nodules ≤ 10 mm in diameter .3, radiomics texture features have no additive value in outcome forecasting. Most early LM lesions are usually small and may therefore not be suitable for radiomics analysis; for a single pulmonary nodule, puncture biopsy is undoubtedly a more appropriate strategy. Nevertheless, when multiple lung nodules (including metastatic and non-metastatic nodules) are present, false negatives can sometimes occur because of sample selection. In summary, analysis of lung nodules cannot always effectively identify the LM status of STS.Radiomics is a promising prospect that involves the extraction of large numbers of high-throughput analysis features from medical images, and can consequently be used to screen for vital features for use in models for quantitative oncology diagnostics , 15. AltPast studies have suggested that tumor-related risk factors, such as the grade of malignancy and size of the tumor, are prognostic factors for the DM status of STS , 19. AltThe purpose of our study was therefore to construct a DL radiomics nomogram (DLRN) using a three-center dataset for the preoperative prediction of LM status in STS.th Edition). Pathological results were confirmed by a pathologist (F.H.) with 12 years of experience in soft tissue disease diagnosis. The final histopathologic results of the 242 STS patients are shown in All organizations that participated in this retrospective study achieved approval from their hospital ethics review board and a waiver for the provision of written consent. A total of 351 patients were retrospectively identified for enrollment into this study. All patients underwent preoperative MRI and chest CT examinations at one of three hospitals and were confirmed as having STS by postoperative pathology between May 2008 and September 2020. All patients underwent preoperative MRI examinations, including axial T1-weighted imaging (T1WI) and axial fat-suppressed T2-weighted imaging (FS-T2WI). http://www.itksnap.org). A total of 1379 HCR features were derived from each ROI  was applied to select the top 15 features. Then, the least absolute shrinkage and selection operator (LASSO) algorithm was used to further screen the feature parameters. The LASSO algorithm compresses the regression coefficients of some features to zero, and a 10-fold cross verification method was applied to select the best weight coefficient λ. The selected features were combined with their respective coefficients using a linear combination formula to form the radiomics model. Five machine-learning classifiers were compared: logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting; and the method with the best prediction performance was used to construct a predictive radiomics signature.Finally, the following prediction models were built: (1) an HCR model, including T1WI and FS-T2WI handcrafted radiomics features; (2) a DL model, including T1WI and FS-T2WI DL extracted features; and (3) a handcrafted and radiomics-DL combined (HD-Combined) model, including both HCR features and DL features from T1WI and FS-T2WI. Each machine-learning model was first trained without subsampling and then retrained with the synthetic minority oversampling technique (SMOTE) , 29.The statistically significant preoperative clinical characteristics were screened using univariate logistic analysis. Characteristics with P < 0.10 were then entered into a multivariate logistic regression. Those characteristics with a P value < 0.05 were identified as independent predictors for a risk of LM and were used to establish a preoperative clinical model. Finally, the independent risk predictors and the best performing radiomics signature model were combined to construct the DLRN.The area under the receiver operating characteristics curve (AUC) and accuracy were used to access the LM-status prediction capability of the clinical model, radiomics signature models, and DLRN when they were applied to the training set and external validation set. The DeLong test was performed to evaluate the difference of each model’s AUC. Calibration curves were used to assess the fitting of the models. The clinical reliability and practicability of the models were evaluated by decision curve analysis (DCA).Postoperative follow-up examinations of the patients using MRI or CT were performed every 3–6 months for the first 2 years and then once a year subsequently. The time from operation to the time of the patient survival endpoint outcome, such as imaging examination identification of lesion recurrence, day of last follow-up examination, or day of death with no evidence of progression, was counted as progression-free-survival (PFS). The censoring criteria for the patients were no matter emigration, or the 31 October 2020, whichever came first.Kaplan-Meier survival curves were used for PFS analysis, and the log-rank test was used to analyze the survival situation and compare the PFS probability of patients in different metastasis risk groups. The DLRN model was enrolled into the PFS stratification evaluation.http://www.r-project.org) and R packages we used in each step were shown in t-test was used for continuous variables and the chi-square test for class-based variables. Uni- and multi-variate logistic analysis were applied in SPSS software .All statistical procedures were performed using R software , and these were combined with 54 T1WI-DL features and 50 FS-T2WI-DL features for inclusion in the subsequent investigations. In the screening with the mRMR-LASSO algorithm, one HCR feature and five DL features had non-zero coefficients and were used in the HD-Combined model , better clinical application, and was well calibrated. Additionally, the DLRN provided satisfactory PFS risk stratification of the patients.In a previous study, Li  et al. fRadiomics is a promising approach that involves the extraction of large numbers of high-throughput analysis features, consequently allowing screening for vital features for use in models for quantitative oncology diagnostics , 32. In The best-performing HD-Combined model included 1 HCR feature and 5 DL features, suggesting that the DCNNs may have derived quantitative information reflecting the risk of LM occurring in STS. As displayed in In terms of simplicity and efficiency, we combined the mRMR and LASSO feature screening with five classifiers to establish the machine learning algorithm. The mRMR method is a novel feature screening algorithm that can screen radiomics features with more credible coefficients and fewer redundancies . LASSO iLM masses were present in less than 20% of the patients with STSs, and therefore a data unbalance problem cannot be ignored. An unbalanced sets problem can potentially generate a negative effect on the application of machine-learning classification approaches , 41, andDM occurs in approximately 25%–30% of patients with STS . In our Another discovery was that the current DLRN showed satisfactory risk stratification performance for the PFS of patients in the training and external validation sets, which reflects the reality that STS patients with LM have a poor prognosis , 3. PastThe current study had several limitations. First, selection bias may occur whenever strict criteria are applied. Second, our study only contained patients from China. STS can have different biology and etiology in different races or countries; how this would affect our nomogram is unknown. Third, because of the small number of patients who underwent contrast-enhanced MRI scans, contrast-enhanced images were not included in our study. Further MRI sequences, such as dynamic contrast-enhanced MRI, diffusion-weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion, could be collected and included in future studies to improve the model. Finally, although pleasing external validation results were acquired in our study, a large number of Gordian techniques in radiomics flow  need to be enrolled in further studies to enhance the robustness and generalization of the radiomics model.In conclusion, the current DLRN had good performance for predicting LM status in STS, and could offer essential information for formulating the treatment strategy.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.H-YL and S-FY have contributed equally to this work. D-PH and H-XW conceptualized the study. H-MZ, H-XW, and D-PH contributed to the methodology and validated the study. S-LL, S-FY and L-SD organized the database. H-YL, C-CH and J-XX contributed to the formal analysis and the statistical analysis. H-YL and S-FY wrote and prepared the original draft. All authors wrote and prepared the original draft. D-PH, H-XW and S-FY supervised the study. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (Grant No. 82172035). This study was funded by the Project Grant No. ZR2020MH286 and No. ZR2021MH159 supported by the Shandong Provincial Natural Science Foundation. This study was funded by the Clinical Medicine +X Project of the Affiliated Hospital of Qingdao University (Grant No. QDFY+ X2021015). This work was supported by the Medicine and Health Technology Development Program of Shandong Province (Grant No. 2019WS373).Authors C-CH and J-XX were employed by Beijing Deepwise & League of PHD Technology Co., Ltd.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


If the negative emotions experienced in life become trauma, they affect daily life. Neuro-feedback technology has recently been introduced as a treatment, but many different neuro-feedback protocols and methods exits. This study conducted a meta-analysis of neuro-feedback training for post-traumatic stress disorder (PTSD) symptoms to evaluate the effects of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG)-based neuro-feedback training. A search of PubMed, the Cochrane Library, Web of Science, Science Direct, and ClinicalTrials.gov was conducted from January 2011 to December 2021. The studies’ quality was assessed using the Cochrane risk of bias tool and publication bias was assessed by Egger’s regression test. Seven studies that met the inclusion criteria were used for the systematic review and meta-analysis. EEG was more effective than fMRI for PTSD symptoms, and the effect on PTSD symptoms was higher than on anxiety and depression. There was no difference in the effectiveness of the training sessions. Our findings showed that EEG-based neuro-feedback training was more helpful for training PTSD symptoms. Additionally, the methods were also shown to be valid for evaluating clinical PTSD diagnoses. Further research is needed to establish a gold standard protocol for the EEG-based neuro-feedback training (EEG-NFT) method for PTSD symptoms. Many individuals fail to endorse their negative reactions at the time of an event . It is eFor PTSD, self-regulation, increased neuroplasticity, and the recapture of the brain’s functional network are the primary factors which are important in healing . Neuro-fPTSD symptoms derive from several areas of the brain. Abnormal contextual processing is often observed in patients with PTSD and it relies on the functional integrity of the medial prefrontal cortex (PFC), hippocampus, and amygdala . A previMany different NF protocols and methods exist . NF by bThe studies were identified through comprehensive searches of PubMed, the Cochrane Library, Web of Science, Science Direct, and ClinicalTrials.gov databases conducted from January 2011 to December 2021. The search string was structured using the PICOS method: P (population) = the patients for PTSD, I (intervention) = neuro-feedback training, C (comparison) = sham, other cognitive training, control group, or no intervention, O (outcome) = PTSD symptoms, anxiety, depression, and S (study design) = randomized controlled trials (RCTs). The search terms were trauma OR (PTSD OR post-traumatic stress disorder) AND (neurofeedback training OR NF-training OR NFT).(1)Language: English;(2)Design: RCT;(3)Intervention: fMRI-NFT, EEG-NFT of alpha activity, e.g., alpha peak amplitude, alpha-theta ratio, or alpha and theta activities;(4)Control group: PTSD patients who received other treatments, sham-NFT, or no intervention;(5)Participants: PTSD patients;(6)Evaluation: assessments of PTSD, anxiety, and depression.We combined the search results from five different databases and deleted duplicate records. Studies were included if they met the following criteria:Studies were ineligible if they were not written in English or were conference abstracts or were not full texts.p-values of <0.05 were considered to indicate the presence of the bias).The studies’ quality was assessed using the Cochrane risk of bias (RoB) tool  in randomized controlled trials (RCTs). We determined the quality of each study according to the selection bias, allocation, detection bias, performance bias, attrition bias, and reporting bias. Three levels  of a risk of bias were evaluated. To determine if there was any bias in the individual results included in this study, publication bias was assessed by the visual inspection of funnel plots and by Egger’s regression test (two-tailed (1)No control group design;(2)Intervention: cognitive tasks with no NFT, no EEG-NFT, or no fMRI-NFT;(3)Control group: healthy population;(4)Evaluation: data without assessment tools.Data were extracted in duplicate using standardized data extraction forms. Information was gathered on the study’s design, participants, NFT characteristics , and results. The outcomes were PTSD diagnosis, anxiety, and depression in PTSD participants. Studies were excluded if they met the following criteria:p < 0.05 indicated notable heterogeneity, and a random effect model was used [All analyses were conducted using Comprehensive Meta-Analysis 2.0 software . We analwas used . Second,A total of seven records met the criteria for qualitative synthesis . Studiesp < 0.05) with a high heterogeneity . In contrast, fMRI-NFT  showed low heterogeneity . p = 0.711, p < 0.05) (p > 0.05).Of these PTSD diagnosis assessments, CAPS, PCL-5, and DTS were from EEG-NFT and CAPS and PCL-M were from fMRI-NFT. The effect and heterogeneity tests showed that there was no heterogeneity  . Figure p = 0.013, p > 0.05) (p > 0.05)  . However > 0.05) .p = 0.29661).All of the studies included in this paper experimented with NFT for PTSD participants, and the length of the NFT sessions was different. Therefore, the sessions’ length was broadly divided into short sessions and long sessions. There were three to seven sessions in the short-session group and 16 to 25 sessions in the long-session group. This study aimed to analyze whether NFT was effective in PTSD participants by dividing methods into EEG and fMRI as representative techniques, and whether there was a clinical improvement effect in a diagnosis evaluation and an anxiety and depression evaluation of PTSD symptoms. We found that EEG-NFT was more effective in improving PTSD symptoms than fMRI-NFT, and the effectiveness of NFT was significant in the scores seen in the PTSD diagnostic evaluations.A previous study  reportedPTSD causes cognitive and emotional problems, including negative self-beliefs and expectations and an inability to experience positive emotions . There iStudies on NFT as a method of treating PTSD were analyzed. Twenty-four sessions of EEG-NFT led to significant improvements in PTSD symptoms and emotion regulation . NicholsTaken together, in the current study, out finding showed that EEG-NFT was more likely to affect PTSD symptoms than fMRI, and NFT was found to be more effective in PTSD diagnosis than anxiety and depression. However, care should be taken with the interpretation of our results. Because of our small sample size, the results of the publication bias and the effect size are less reliable .Since the gold standard protocol for NFT used to treat PTSD symptoms remains unclear, future studies are needed to examine the effectiveness of different sessions, brain target-regions, and training protocol methods on PTSD symptoms.We explored the effect of neuro-feedback training on PTSD symptoms. Our findings indicated that EEG-based neuro-feedback training was more helpful to train PTSD symptoms than fMRI-based neuro-feedback training. Moreover, this effect suggests that it is also valid for the evaluation of PTSD symptoms for clinical diagnoses. This meta-analysis study demonstrates the potential for affecting PTSD symptoms using EEG. Further research to establish a gold standard protocol for EEG-based neuro-feedback training for PTSD symptoms is needed.


Piwi-interacting RNAs (piRNAs) are regarded as drug targets and biomarkers for the diagnosis and therapy of diseases. However, biological experiments cost substantial time and resources, and the existing computational methods only focus on identifying missing associations between known piRNAs and diseases. With the fast development of biological experiments, more and more piRNAs are detected. Therefore, the identification of piRNA-disease associations of newly detected piRNAs has significant theoretical value and practical significance on pathogenesis of diseases. In this study, the iPiDA-LTR predictor is proposed to identify associations between piRNAs and diseases based on Learning to Rank. The iPiDA-LTR predictor not only identifies the missing associations between known piRNAs and diseases, but also detects diseases associated with newly detected piRNAs. Experimental results demonstrate that iPiDA-LTR effectively predicts piRNA-disease associations outperforming the other related methods. Accumulating evidences have indicated that dysfunction and abnormal expression of piRNAs are closely associated with the emergence and development of diseases. Currently, identifying piRNA-disease associations mainly focuses on biological experimental methods and computational methods. However, biological experimental methods take substantial time and resources. Computational methods mainly focused on identifying diseases associated known piRNAs. With the development of biological technology, more and more newly detected piRNAs were detected. Therefore, identifying diseases associated with newly detected piRNAs is more important compared with identifying diseases associated with known piRNAs. Information retrieval (IR)’s goal is to rank documents based on the relevance to certain topics. This task is particularly similar with identification of piRNA-disease associations. Specifically, ranking documents related to previous topics corresponds to identify diseases associated with known piRNAs, and ranking documents related to novel topics is similar to identify diseases associated with newly detected piRNAs. Therefore, we propose a new predictor called iPiDA-LTR to predict associations between piRNAs and diseases based on information retrieval technology. Experimental results indicated that iPiDA-LTR is promising in identifying diseases associated with known piRNAs and newly detected piRNAs. PLOS Computational Biology Methods paper.This is a Piwi-interacting RNA (piRNA) with 24–31 nucleotides in length is a class of small RNAs interacting with Piwi-subfamily Argonaute proteins . With thAs more and more piRNA functions were detected, many evidences indicated that dysfunction and abnormal expression of piRNAs are closely associated with the emergence and development of diseases –17. Therf between query q and document d. Therefore, this task is particularly similar with identification of piRNA-disease associations . PiRNAs and diseases can be treated as queries and documents, respectively. Learning to Rank not only identifies associations between known piRNAs and diseases, but also ranks diseases associated with newly detected piRNAs.In recent years, information retrieval (IR) becomes a widely used technology, whose ultimate goal is to rank documents based on the relevance to certain topics , 31. As http://bliulab.net/iPiDA-LTR.In this study, we propose a new predictor, named iPiDA-LTR, to predict associations between piRNAs and diseases, which has the following advantages. iPiDA-LTR predictor combines component methods and Learning to Rank, which cannot only identify missing associations between known piRNAs and diseases, but also can identify diseases associated with newly detected piRNAs. Experimental results indicated that iPiDA-LTR is promising to identify piRNA-disease associations. A web server of iPiDA-LTR is constructed to identify diseases associated with query piRNAs, which can be accessed at To imitate two application scenarios, we construct two types of datasets based on piRDisease v1.0 database  collectiollowing , which cons from . Pall anBenchmark dataset and independent dataset are constructed as:Table 1. The datasets can be obtained at http://bliulab.net/iPiDA-LTR/dataset/.To imitate the second application scenario, we randomly select 80% and 20% piRNAs from Fig 2 with three steps: (a) Association feature extraction; (b) Component methods; (c) Ranking diseases associated with query piRNAs.In this study, a novel ranking framework, named iPiDA-LTR, is proposed to solve two application scenarios. The workflow of iPiDA-LTR is shown in SP is similarity between piRNA pi and piRNA pj. SW represents local alignment score between piRNA pi and piRNA pj based on Smith-Waterman algorithm.The piRNA similarities play a vital role in RNA-disease association identification –26, and SD is similarity between disease m and disease n. Tk represents the node set containing the ancestor nodes of k and itself. Sn(i) is the semantic value of node i to node n.The disease semantic similarity calculation is a key component in RNA-disease association identification. The disease ontology  has beend and the query piRNA p is:p and disease d. SP and SD represent pth row and dth row in the SP and SD, respectively. If piRNA p is associated with disease d, the label of The association feature between disease Eq 7) are used to train machine learning models, and then used to calculate association scores for p and disease d can be represented as:p and disease d. p and disease d calculated by CF, LR, RF and SVM, respectively.In this study, we select two types of component methods to calculate association scores, including machine learning methods and collaborative filtering (CF). For machine learning methods, Random Forest (RF) –60, Logik, shrinkage and the number of leaves are the four main parameters. The truncation level of k influences the quality of top-ranked results by Normalized Discounted Cumulative Gain (NDCG), which can be formulated as [k represents the truncation level. IDCG@k is the value of DCG@k in the best optimal ranking results. If a query piRNA is associated with disease located in position i, reli is equal to 1, otherwise 0. To obtain the final ranking results, association scores calculated by Eq 8 for training set are used to train LambdaMART model, and the trained LambdaMART model is employed to rank diseases associated with query piRNAs based on association scores of query piRNAs.In this study, we employ Learning to Rank (LTR) to solve the problem of identifying potential piRNA-disease associations motivated by information retrieval , 38, 67.lated as :{DCG@kk. Besides, Area Under the ROC Curve (AUC) and Area Under the Precision-Recall Curve (AUPR) are also used to measure comprehensive performance [In this study, the benchmark dataset is employed to optimize the parameters of the models, and the independent dataset is used to evaluate the performance of predictors. How to evaluate the ranking quality and prediction performance is crucial for identifying piRNA-disease associations. Because iPiDA-LTR predictor treats the identification of piRNA-disease associations as an information retrieval ranking task, we employ three important ranking criteria to evaluate the rank quality of different predictors: Normalized Discounted Cumulative Gain (NDCG), Mean Average Precision (MAP) and ROCformance –72. The k, shrinkage and the number of leaves. Due to the large number of combinations of the four parameters, we fix three parameters in turns, and then find the local optimal values of the remaining parameters according to AUPR. The influences of different combinations of parameters for iPiDA-LTR on Figs 3 and 4, respectively, from which we can see that the final optimized combinations of four parameters on iPiDA-LTR predictor on iPiDA-LTR predictor mainly contains the following four parameters: the number of trees, the truncation level Tables 2 and 3, from which we can see the followings: (i) iPiDA-LTR predictor outperforms iPiDA-LTR-ML predictor on Table 3). Machine learning methods based on classification algorithms focus on global predictive performance, and collaborative filtering can identify special piRNA-related diseases focusing on local predictive performance. Therefore, machine learning methods and collaborative filtering are complementary. It is not surprising that iPiDA-LTR predictor obtains the best performance compared with iPiDA-LTR-ML, because iPiDA-LTR shares the advantages of these two types of methods.In this study, iPiDA-LTR incorporates two types of component methods, including machine learning methods  and collaborative filtering (CF). LR, RF and SVM are obtained by python package Scikit-learn . For LR’Fig 5 shows the usage frequencies of component methods on iPiDA-LTR, from which we can see that each component method is frequently used, indicating that they are important for iPiDA-LTR. Tables 2 and 3 and Fig 5 show that component methods are complementary, and iPiDA-LTR combines them leading to better performance for identifying piRNA-disease associations.The usage frequencies of component methods measure the contribution of component methods for iPiDA-LTR. Tables 4 and 5, from which we can see that iPiDA-LTR is better than the other methods, indicating that iPiDA-LTR is more suitable for identifying piRNA-disease associations. Researchers tend to focus on the top ranked predicted associations in practical application scenarios. Therefore, we analyze the quality of the predicted results , from which we can see that iPiDA-LTR outperforms the other predictors in terms of ROC1-ROC10. It is not surprising because the loss function of LambdaMART NDCG mainly focuses on the top-ranked predictive known associations (see Eq 9).In this section, the two state-of-the-art predictors including iPiDi-PUL predictor  and iPiDTo illustrate the predictive performance of iPiDA-LTR predictor for the identification of associations between new piRNAs and diseases, two query piRNAs, including piR-hsa-23210 and piR-hsa-15023, are selected as query piRNAs from Tables 6 and  respectively, from which we can see the followings: (i) The evidences for the top five predicted piR-hsa-23210-associated diseases are supported by PubMed (https://pubmed.ncbi.nlm.nih.gov/). For example, the target gene of piR-hsa-23210 is SMC5, which plays crucial roles in the process of human spermatogenesis, such as on the synaptonemal complex between synapsed chromosomes, and in the development of spermatogonial cells [Table 7 have been proved to be associated with piR-hsa-15023. For example, Busch et al. found that piR-hsa-15023 is down-regulated in renal cell carcinoma [The predicted results of piR-hsa-23210 and piR-hsa-15023 are shown in al cells . Roy et al cells . (ii) Foarcinoma . piR-hsaarcinoma . Therefohttp://bliulab.net/iPiDA-LTR/. Although iPiDA-LTR effectively predicts piRNA-disease associations, it only integrates basic machine learning methods and collaborative filtering. In future studies, we will integrate the other state-of-the-art methods and features to improve piRNA-disease associations. The LTR-based framework discussed in this study is a general framework, which would have many other applications in bioinformatics, such as protein function prediction, remote homology detection, etc.In this study, we treat the task of piRNA-disease associations as a search task based on Learning to Rank , 68, whe


Backscatter communication (BackCom) constitutes intriguing technology that enables low-power devices in transmitting signals by reflecting ambient radio frequency (RF) signals that consume ultra-low energy. Applying the BackCom technique in large-scale networks with massive low-power devices can effectively address the energy issue observed in low-power devices. Prior studies only consider large-scale BackCom networks equipped with omni-directional antennas, called Omn-BackCom Net. To improve the network’s performance, we employ directional antennas in large-scale BackCom networks, called Dir-BackCom Nets. This article establishes a theoretical model for analyzing the performance of Dir-BackCom Nets. The performance metrics include both connectivity and spatial throughput. Our model is genaralized for both Dir-BackCom Nets and Omn-BackCom Net. The accuracy of our theoretical model is verified by extensive simulations. Results indicate that Dir-BackCom Nets can improve connectivity and spatial throughput. Moreover, results show that the throughput can be maximized by choosing an optimal density of BTs. In addition, both the connectivity and spatial throughput of BackCom Nets can be improved by choosing a directional antenna with a proper beamwidth and gain of the main lobe. Our theoretical model and results can offer beneficial implications for constructing Dir-BackCom Nets. In the era of the Internet of things (IoT), there is an expectation that massive low-power devices will be used in large-scale IoT networks to monitor, sense, and generate information to support various IoT applications such as smart city/factory/agriculture ,2,3,4,5.In large-scale BackCom networks (BackCom Nets), backscatter transmitters (BTs) need to transmit data by reflecting RF signals from ambient energy/signal providers: carrier emitters (CEs) . ConsequIn the performance analysis of BackCom networks, because CEs and BTs are usually distributed with randomness in large-scale networks ,7,8,9,10Different from omni-directional antennas, directional antennas, assisted by beamforming technique, can enhance signals transmission/reception in intended directions and can simultaneously decrease signal transmission/reception in other directions. In peer-to-peer communication applications, due to the beamforming transmission, directional antennas can decrease interferences in undesired directions, thereby potentially improving the connectivity and throughput . Moreove0-BR0, where BT0 receives the energy  provided from CEs and then reflects signals to BR0. We can observe that BT0 receives energy from CE1 and CE2 by different antenna gains, thereby leading to inhomogeneous energy reception in the space around BT0. Then, BR0 receives interference by different antenna gains . In addition, the interference from BT1 and BT3 is transmitted by a high gain, while the interference from BT2 and BT4 is transmitted by a low gain. As a result, the received interference at BR0 from all BT1 to BT4 is different from each other, resulting in the fact that the interference received at BR0 is more spatially inhomogeneous. Therefore, compared with Omn-BackCom Nets where the received energy/interference is spatially homogeneous, the complexity of the performance analysis in Dir-BackCom Nets significantly increased.To the best of our knowledge, there is no study that analyzes the performance of large-scale Dir-BackCom Nets. The performance analysis of large-scale Dir-BackCom Nets is far more complex than large-scale BackCom Nets mounted with omni-directional antennas, called Omn-BackCom Nets. This is because the transmission/reception strength of a directional antenna varies in different directions , leading to the fact that the received energy/interference at a directional antenna in a large-scale network is spatially inhomogeneous. For example, Therefore, the main goal of this paper is to develop a theoretical model to analyze the performance of Dir-BackCom Nets. The main contributions are summarised as follows.In contrast to prior related studies focusing on the performance of Omn-BackCom Nets, we first identify Dir-BackCom Nets. Then, we establish a theoretical model to analyze the performance of Dir-BackCom Nets. This model is general for BackCom Nets equipped with omn-directional antennas or directional antennas.We derive both the connectivity and the spatial throughput of Dir-BackCom Nets. Results indicate that the spatial throughput can be maximized by selecting an optimal density of BTs.We make a comparison of the performance among Dir-BackCom Nets, Omn-BackCom Nets, and networks in which BTs and BRs are equipped with directional antennas and omni-directional antennas, respectively, called Dir-Omn-BackCom Nets. Our results indicate that equipping directional antennas at BTs or BR can improve network performance. Moreover, we perform a comparison of performance among Dir-BackCom Nets equipped with different directional antennas with varied antenna beamwidths and antenna gains. Results show that the performance of Dir-BackCom Nets can be improved by choosing suitable directional antennas with proper antenna beamwidths and gains of the main lobe.The rest of the article is organized as follows: We consider a large-scale Dir-BackCom network as shown in  λBT≫λCE . Then, waired BT .We assume that each BT/BR is mounted with a directional antenna, where the orientation of the directional antenna of a BT/BR is directed towards its paired BR/BT . As a re all BTs . We assu all BTs . When thIt is worth noting that our performance analyses do not consider the devices near network border, because their performance analysis is quite complex due to the fact that their performance is related to the specific shape of the network’s edge . TherefoN. Then, the density of co-channel CEs is In the large-scale Dir-BackCom Net, multiple orthogonal frequency channels can be allocated to CEs. Because available frequency channels are limited while there are massive CEs in the large-scale network, multiple CEs reuse an identical frequency channel. Assume that the number of available frequency channels is r is the propagation distance, h is the small-scale fading factor following an exponential distribution with mean 1 [During propagation, we consider a typical propagation model th 2<α<6 , h is thh mean 1 , and Gt large-scale BackCom Nets. For analytical tractability, similarly to [The antenna gain of an omni-directional antenna, denoted by larly to ,26,27,28To assure the generality of our model, we consider that directional antennas equipped by BTs and BRs can have different values of both reflection coefficient and is denoted by C is a constant to ensure a zero-input or zero-output response at the energy harvester, RF signals used for energy harvesting can be stored at BTs by a energy harvester. Following ,31,32, wThe harvested energy of BTs  and the probability density function (PDF) of the received power at a BT  at the BR is not less than a threshold I). The region where a BR receives interference by the main lobe within The region where a BR receives interference by the side lobe within Next, we derive the Laplace transforms Let 1 in 2 in 0 denote the BT paired with the BR being studied. Then, the received interference at the studied BR in region j and the studied BR, and j and the studied BR.We first analyze the received interference from region Similarly, the received interference at the BR from region With the received interference Lemma 1.The Laplace transform where Proof. The proof is provided in Finally, the connectivity of large-scale Dir-BackCom Nets can be given by the following Theorem.Theorem 1.The connectivity of large-scale Dir-BackCom Nets can be expressed as follows:where Proof. After inserting both Equations  and 9)  9) into Remark 2.The connectivity given by Equation  is generEquation  that theConsidering our BackCom Net is a large-scale network, we adopt the spatial throughput as the metric of the network throughput ,35. The Definition 2.The spatial throughput of BackCom Nets is the throughput of BTs within a unit area of the network space.The spatial throughput of large-scale Dir-BackCom Nets can be expressed by the following.Theorem 2.The spatial throughput of large-scale Dir-BackCom Nets is given by the following:where Equation  needs toProof. The proof is provided in We conduct simulations to verify our proposed analytical model. Specifically, we adopt commercial software MATLAB as our simulation tool. In simulations, fixed parameters/factors are provided in Dir-Omn-BackCom Nets is always higher than Omn-BackCom Nets under different path loss environments (i.e., Dir-BackCom Nets is higher than Dir-Omn-BackCom Nets under different values of In this group, we investigate the impact of different directional antennas on the performance of Dir-BackCom Nets. Specifically, we consider that these different directional antennas possess different beamwidths. Meanwhile, similarly to , the conThis article establishes a theoretic model to analyze the performance of large-scale Dir-BackCom Nets, where both BTs and BRs are equipped with directional antennas. The performance metrics include both connectivity and spatial throughput. Our theoretic model is general for BackCom Nets where BTs/BRs are equipped with directional antennas or omni-directional antennas. The accuracy of our theoretic model is verified by extensive simulations. In conclusion, this paper provides the following major findings:Equipping directional antennas instead of omni-directional antenna at BTs can improve the active probability.Employing directional antennas at either BTs or BRs can improve the connectivity and spatial throughput of BackCom Nets.The spatial throughput can be maximized by choosing an optimal density of BTs.Both the connectivity and spatial throughput of BackCom Nets can be improved by choosing a directional antenna with a proper antenna beamwidth and gain of the main lobe.


Caregivers without CSSs tended to receive a smaller amount of assistance with a lower frequency (p < 0.05). The number of participants with an adequate environment and equipment was significantly less in the moderate/severe CSS group (p < 0.01). Thus, our findings may suggest that CSS severity is associated with LBP intensity, widespread pain, psychological factors, and work status in caregivers.Low back pain (LBP) is associated with psychological factors and central sensitization-related symptoms (CSSs). The relationship between CSSs, LBP-related factors, and work status in caregivers remain unclear. This multicentre, collaborative, cross-sectional study aimed to determine the association between CSS severity, LBP-related factors, and work status in caregivers with LBP. We measured LBP intensity, pain duration, pain sites, CSSs , psychological factors , and work status  in 660 caregivers. CSS severity was categorised as no (CSI-9:0–9), mild (CSI-9:10–19), or moderate/severe (CSI-9:20–36). We further performed multiple comparison analyses and adjusted the residual chi-square to reveal differences between CSS severity groups. Caregivers with more severe CSSs tended to exhibit worse LBP intensity ( Low back pain (LBP) is one of the most common causes of disability worldwide . LBP alsThe severity and disability due to LBP are associated with several factors, including psychological, social, and biophysical factors; comorbidities; and pain processing mechanisms . PsycholThe physical effects of CSSs on caregivers have not been fully clarified, and the association between LBP and CSSs in caregivers is unknown. In addition, the association between caregivers’ work status and CSSs has not yet been clarified. In other words, previous studies have not fully clarified the effects of CSSs on LBP and the work environment among caregivers. Identifying these relationships may lead to reconsideration of LBP management in caregivers. We hypothesised that severe CSSs are associated with negative LBP-related factors and an inadequate work environment. This study aimed to determine the association of CSS severity with LBP-related factors and work status in caregivers with LBP.This multicentre, collaborative, cross-sectional study was conducted between 1 July and 30 September 2021. A total of 1214 caregivers were recruited from 35 centres. Respondents who self-completed the questionnaires totalled 1064 workers (response rate: 88.1%). The exclusion criteria were foreign workers, no LBP, and an incomplete assessment. The 660 caregivers with LBP who completed the self-administered questionnaire with no missing data were included in the analysis . The samThe following characteristics were assessed for each patient: demographics , question items related to pain, CSSs ), cognitive-emotional factors  and Pain Self-Efficacy Questionnaire (PSEQ)), and question items related to work status.The five question items related to pain are as follows: (i) presence/absence of low back pain (yes/no); (ii) duration of LBP (<3/≥3 months); (iii) pain intensity for LBP in the last week  ); (iv) pain intensity for LBP before becoming caregivers ; and (v) pain sites (head/neck/shoulder/back/hip/knee/ankle) other than the LBP.The CSI-9, a shorter version of the 25-item CSI, has nine items and was used to assess health-related symptoms of CSSs . Higher The PCS was used to assess catastrophic thinking . Higher The PSEQ was used to assess self-efficacy regarding pain . A lowerThe four question items related to work status are as follows: (i) interference with work due to LBP (categorised as no interference with work/presenteeism related to LBP/absenteeism related to LBP); (ii) amount of assistance needed for transferring (very little/light assistance/full assistance); (iii) frequency of back-straining movements , movements occurring less than or equal to 10 times per hour or continuous movements that are a little burdensome , and movements that were less than a few times per day ); and (iv) environment and equipment to prevent LBP (prevention measures are adequate (adequate), prevention measures are somewhat in place but insufficient (adequate but insufficient), and prevention measures are inadequate (inadequate)).We divided the participants into three groups based on their CSI-9 score as follows: no, mild, and moderate/severe CSS groups with CSI-9 scores of 0–9, 10–19, and 20–36 points, respectively .We used a Kruskal–Wallis test and multiple comparisons to compare continuous variables between severity groups using Bonferroni’s adjustment method to optimize protection against type 1 errors. The chi-square test was used to compare categorical variables between the severity groups. Then, we calculated the adjusted chi-square residuals considering 1.96 to be a critical value (α = 0.05). Adjusted residuals can be used to determine the significant contributor to a significant chi-square result.We analysed the following categorical variables: For question items related to LBP, we divided participants into two groups based on LBP duration . In addition, we divided the participants into three groups based on the LBP intensity . For cognitive-emotional factors, we analysed PCS and PSEQ scores both as categorical and continuous variables. We divided the patients into two groups based on the PCS cut-off score  and PSEQ cut-off score . We divided the participants into two groups based on whether there was interference with work due to LBP (no interference vs. interference (presenteeism and absenteeism)).p < 0.05.Statistical analyses were performed using R (ver. 3.6.1). The level of significance was set at The participants’ characteristics are summarized in In terms of pain duration, the number of caregivers with acute LBP was significantly more than those with chronic LBP in the no CSS group , but wasRegarding interference with work due to LBP, the number of participants who experienced interference with work was significantly higher in the moderate/severe CSS group. Regarding the amount of assistance needed for transferring, the number of participants requiring very little assistance was significantly higher in the no CSS group. The frequency of back-straining movements was significantly more in the moderate/severe CSS group. The number of participants with an adequate environment and equipment was significantly less in the moderate/severe CSS group.We used multiple comparison analyses and adjusted chi-square residuals to investigate the relationships between CSSs, LBP-related factors, and work status in caregivers. The results demonstrated that caregivers with severe CSSs tended to have worse LBP intensity, widespread pain, catastrophic thinking, and pain self-efficacy. Regarding work status, caregivers with more severe CSSs tended to experience interference with work. In addition, caregivers with no CSSs tended to receive a smaller amount of assistance and assistance frequency. Interestingly, the number of participants with an adequate environment and equipment was significantly less in the moderate/severe CSS group.This study aimed to investigate the association between CSS severity and LBP-related factors. In previous studies, severe CSSs were associated with pain severity and chronicity ,20. It wAnother feature of this study was the investigation of the relationship between CSS severity and work status among caregivers. The results of the present study showed that many caregivers with moderate/severe CSSs reported interference with work. CSSs have been considered a factor associated with the difficulty of work retention in a previous study , and theThe present study is the first to demonstrate an association between CSSs, LBP-related factors, and work status in caregivers with LBP. Previous studies have not fully clarified the effects of CSSs on LBP and the work environment among caregivers. The present study is unique because it comprehensively examined the effects on LBP and work status, including CSSs. Our findings may suggest that CSS severity is associated with LBP severity, psychological factors, and work status, including interference with work. Focusing on CSS management, the effectiveness of pain neuroscience education and lifestyle supervision has been reported ,27,28. CThis study has several limitations. (1) The outcomes were assessed using self-reported questionnaires, which might have resulted in subjective bias. Especially for the survey on the work environment and equipment, it is possible that individual criterion bias affected the verbal rating scale because of the lack of specific criteria . (2) The current study used a cross-sectional study design, and it was not possible to design an intervention based on a longitudinal course. Examining causal relationships based on a longitudinal course is necessary in future studies. Revealing this causal relationship may lead to the development of better management for individuals and institutions, including CSS support.To our knowledge, this is the first study to investigate associations between CSSs, LBP-related factors, and work status in caregivers with LBP. Our findings may suggest that CSS severity is associated with LBP intensity, widespread pain, psychological factors, and work status, including interference with work; this knowledge can help improve the management of caregivers with LBP.


The prognosis of patients with brain metastases has dramatically improved, and long-term tumor control and reduction of the risk of late toxicities, including neurocognitive dysfunction, are important for patient quality of life. Stereotactic irradiation for multiple brain metastases, rather than whole-brain radiotherapy, can result in high local control rate with low incidence of neurocognitive deterioration and leukoencephalopathy. Recent advances in radiotherapy devices, treatment-planning systems, and image-guided radiotherapy can realize single isocenter stereotactic irradiation for multiple brain metastases (SI-STI-MBM), in which only one isocenter is sufficient to treat multiple brain metastases simultaneously. SI-STI-MBM has expanded the indications for linear accelerator-based stereotactic irradiation and considerably reduced patient burden. This review summarizes the background, methods, clinical outcomes, and specific consideration points of SI-STI-MBM. In addition, the prospects of SI-STI-MBM are addressed. Brain metastases are common in cancer patients, with an incidence of 9.6% of all cancer patients . Brain mWhole-brain radiotherapy (WBRT) used to be the sole standard radiotherapeutic approach for patients with brain metastases, and the intent and irradiation dose of WBRT are palliative rather than curative. This is because the whole brain is irradiated during WBRT, and ablative doses to the whole brain inevitably result in severe acute and late toxicities. Despite only palliative irradiation doses, neurocognitive dysfunction and leukoencephalopathy due to WBRT should be considered, because these late complications are sometimes observed and directly affect patient’s lives . RecentlStereotactic irradiation was developed and clinically used as an alternative ablative radiotherapy option for intracranial lesions using the Leksell Gamma Knife System for gamma knife radiosurgery (GKS) . In addiPrognosis of patients with brain metastases was limited before 2000s. In 1997, Gasper et al. reported the recursive partitioning analysis (RPA) classification, which showed the prognosis of patients with brain metastases treated with radiotherapy . The surThereafter, other prognostic classifications have been published: GPA , diseaseTo improve the prognosis of patients with brain metastases, clinicians should pay more attention to late toxicities caused by radiotherapy. Neurocognitive dysfunction is a major and serious late complication of WBRT . In cont3 or less and a longest diameter of 3.0 cm or less. In addition, the cumulative volume of all tumors was limited to 15.0 cm3 or less. Based on the JLGK0901 study, the NCCN guidelines developed the concepts of “limited brain metastases” and “extensive brain metastases” in 2018. “Limited brain metastases” is defined as a group of patients for whom SRS is equally effective and offers significant cognitive protection when compared with WBRT. SRS is preferred over WBRT in patients with limited brain metastases. Thus, up to ten brain metastases are now often treated with stereotactic irradiation.In several randomized control trials involving patients with WBRT and stereotactic irradiation, the overall survival in patients with 1–4 brain metastases was similar regardless of whether the patients received WBRT and/or stereotactic irradiation –22. AlthIn LINAC-based stereotactic irradiation, brain metastases are conventionally treated with conformal arcs, one by one . AccordiOwing to advances in image-guided radiotherapy and optimization methods for treatment-planning systems, SI-STI-MBM can be performed in clinical settings . In SI-SCurrently, two irradiation approaches are clinically used for SI-STI-MBM. The first is the volumetric-modulated arc therapy (VMAT) Fig. . By usinThe second approach is to use a treatment-planning device specialized for SI-STI-MBM with conformal arcs  Fig. 2)2). The sSeveral publications have examined the clinical outcomes of SI-STI-MBM for multiple brain metastases , 34–39. While only brain metastases are usually irradiated in SI-STI-MBM, a new approach that combines SI-STI-MBM and WBRT using a simultaneous integrated boost (SIB) method is applied in some institutions , 42. In There are two major physics issues in SI-STI-MBM.99.5% and D0.5% despite the distance between the target and the isocenter in SI-STI-MBM with VMAT when 6D positioning correction was performed using the ExacTrac X-ray system [First, all lesions or all except one target must be offset in SI-STI-MBM. Translational and rotational errors in offset lesions result in larger positional displacement and dose coverage impairment as the distance between the isocenter and center of the target increases –46. Thery system . With rey system . Kraft ey system . In theiSecond, the inaccuracy of small fields generated by the optimization of SI-STI-MBM with VMAT should be considered. The leaf motion in SI-STI-MBM with VMAT is complex, and many small fields are generated for multiple targets. Research on small fields of stereotactic irradiation is ongoing, and information including ICUR 91 supports the QA of stereotactic irradiation for small tumors , 50. AltAdditional evidence is required to evaluate the usefulness of stereotactic irradiation, including SI-STI-MBM. Here, we addressed the prospects of stereotactic irradiation, not limited to SI-STI-MBM, but also including conventional LINAC-based stereotactic irradiation and GKS for multiple brain metastases.First, there is currently limited high-level evidence that directly compares WBRT and stereotactic irradiation in patients with 5–10 brain metastases. Although JLGK0901 showed the usefulness of stereotactic irradiation in patients with 5–10 brain metastases, there were no randomized controlled trials (RCTs) comparing WBRT versus stereotactic irradiation for more than three metastases, before the publication of the Dutch phase III RCT reported by Hartgerink et al. . In a DuSecond, the adaptation of SI-STI-MBM for more than 10 brain metastases is unclear. From a technical perspective, SI-STI-MBM can be adapted for more than 10 brain metastases. However, the superiority or noninferiority of stereotactic irradiation over WBRT in patients with more than 10 brain metastases remains unknown. These two RCTs included patients with more than 10 brain metastases. If these two trials are completed with sufficient statistical power, the treatment strategy for more than 10 brain metastases may change.Finally, brain metastases from small-cell lung carcinoma are controversial in terms of the benefits from stereotactic irradiation. This is because brain metastases from small-cell lung carcinomas tend to occur more frequently than those from nonsmall-cell lung carcinomas. Therefore, WBRT is the standard treatment for brain metastases from cell lung carcinoma. Recently, a multicenter retrospective cohort study named the FIRE-SCLC cohort study was published . In thisAs the prognosis of patients with brain metastases improves, stereotactic irradiation, rather than WBRT, has been performed in many patients to achieve long-term local control and avoid neurocognitive dysfunction due to radiotherapy. Recent advances in radiotherapy devices, treatment-planning systems, and image-guided radiotherapy have enabled SI-STI-MBM to deliver ablative high doses to multiple brain metastases within a short treatment time. In SI-STI-MBM, local control is excellent and the rate of adverse events, including radionecrosis, is tolerable. As SI-STI-MBM uses only one isocenter and many targets are offset, clinicians, physicists, and radiotherapists should reduce translational and rotational errors as much as possible by using a highly precise image-guided technique, including 6D positional correction. High-level evidence regarding stereotactic irradiation for more than 11 brain metastases and brain metastases from small-cell lung cancers will be shown in ongoing clinical trials.


The PPRPS is an independent prognostic factor, and the AUC (Area Under Curve) for 3-year overall survival was 0.748. Combined with age and stage, PPRPS displayed excellent predictive ability. Based on the PPRPS, higher levels of immune cell infiltration, tumor microenvironment, and immune checkpoint molecules were observed in the high-PPRPS group. Furthermore, PPRPS enabled accurate risk prediction for metastatic urothelial carcinoma after anti-PD-L1 monoclonal antibody treatment. Patients in the high-PPRPS group had poor prognoses. Docetaxel, staurosporine, and luminespib were identified as potentially effective drugs for high-PPRPS bladder cancer patients. In summary, we developed the Pan-PCD signature to improve the accuracy of bladder cancer prognostic predictions and to provide a novel classification method to guide treatment selection.Programmed cell death (PCD) refers to a molecularly regulated form of cell death that functions as an essential anticancer defense mechanism and serves as a target of anticancer therapies. Multiple types of PCD comprehensively regulate tumorigenesis and tumor progression and metastasis. However, a systemic exploration of the multiple types of PCD in cancers, especially bladder cancer, is lacking. In this study, we evaluated the expression pattern of genes associated with multiple types of PCD in bladder cancer using the “ssGSEA” method and conceptualized the multiple types of PCD as being collectively involved in “Pan-PCD”. Based on the differentially expressed genes related to Pan-PCD, we developed a Pan-PCD-related prognostic signature (PPRPS) to predict patient prognosis  Bladder cancer is one of the most common cancers and represents the 13th most deadly malignancy worldwide . In 2018Programmed cell death (PCD) is a dedicated form of molecularly regulated cell death that includes apoptosis, necroptosis, ferroptosis, pyroptosis, autophagy, cuproptosis, and other types of programmed cell death, which is in contrast with accidental cell death . And PCDRecently, an increasing number of studies have demonstrated that PCD is tightly correlated with tumorigenesis and treatment , especiaEarly studies of PCD in bladder cancer focused on specific types of cell death, such as necroptosis and pyroptosis . Howeverhttps://portal.gdc.cancer.gov/). A total of 409 subjects and 19 controls were included in our study. Corresponding clinicopathological data of patients were obtained from TCGA Bladder Cancer cohort. Our Pan-PCD gene set comes from the reported multiple types of PCD-related genes, which includes 87 apoptosis genes, 51 necroptosis genes, 59 ferroptosis genes, 39 pyroptosis genes, 136 autophagy genes, and 6 cuproptosis genes (http://timer.compgenomics.org/). The m6A-related gene list was obtained from a previous study (Bladder cancer transcriptome data were downloaded from The Cancer Genome Atlas (TCGA)  between tumor and control specimens were screened using the “edgeR” R package. Here, log2|fold change>1| and an adjusted p value (padj) <0.05 were established as the cutoff values. The R package “ggplot2” was used to visualize the volcano plots and box plots of DEGs. Heatmaps were generated using the R package “pheatmap”.Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore potential molecular processes and biological pathways related to Pan-PCD in bladder cancer. These analyses were performed using the R package “clusterProfiler” for all Pan-PCD-related DEGs. The p values < 0.05 were considered statistically significant.The prognostic value of PCD genes in the TCGA-BLCA cohort was investigated by univariate Cox regression analysis. Multivariate Cox regression analysis was subsequently performed to identify independent prognosis-related genes, and we constructed the Pan-PCD-related prognostic signature. A Kaplan–Meier plot of survival curves was utilized to evaluate the survival probability of the low- and high-PPRPS groups. Using the “timeROC”, “survival”, and “survminer” R packages, the time-dependent receiver operating characteristic curve (ROC) curve was drawn based on the calculated PPRPS score. The area under the curve (AUC) represents the 1-, 2-, and 3-year overall survival (OS) probability to estimate the accuracy of the predicted survival probability and the actual observation rate.We obtained the clinical parameters of patients from TCGA-BLCA cohort. These clinical variables and PPRPS were combined and analyzed in the regression model. Univariate and multivariate Cox regression models were utilized to investigate independent prognostic factors. Forest plots were used to show the results of univariate and multivariate Cox regression analyses using the “forestplot” R package.A nomogram was generated to visualize PPRPS and for use in clinical applications. To evaluate the value of clinical characteristics in predicting the OS probability of bladder cancer patients, we developed multiple decision curves based on the clinical characteristics, PPRPS, and combined clinical-PPRPS models. The clinical application could be determined by quantifying the net benefits at different threshold probabilities.To further explore the difference in the Pan-PCD-related prognostic signature, gene set enrichment analysis (GSEA) was performed to investigate the Pan-PCD-related prognostic signature with P values < 0.05 indicating enrichment for significant functional annotation. The detailed parameters were described in a previous study . The annThe difference in tumor-infiltrating immune cells between the two PPRPS groups was estimated based on the following 7 algorithms: CIBERSORT, TIMER, CIBERSORE-ABS, MCPCOUNTER, QUANTISEQ, XCELL and EPIC. In addition, the characteristics of the tumor microenvironment were also evaluated through scoring with the “ssGSEA” method. Furthermore, a few checkpoint molecules were analyzed to investigate the differences between the low- and high-PPRPS groups.t-test was used.m6A modification regulates the expression level of PCD genes. We selected 12 m6A RNA methylation regulators, including 2 erasers (ALKBH5 and FTO), 5 writers , and 5 readers . To identify the expression differences in m6A regulators between the low- and high-PPRPS groups, a The IMvigor210 cohort was used to assess the effect of anti-PD-L1 immunotherapy. The best overall response was defined as the best response recorded from the start of the treatment until disease progression/relapse. The best overall response was summarized by response category as follows: complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). The Kaplan–Meier method was used to estimate OS rates.https://www.cancerrxgene.org/), we predicted the chemotherapy response of each sample. Twenty anticancer drugs effective against bladder cancer were selected. The analysis was performed using the R package “oncoPredict”. The IC50 of each sample was estimated, and the different IC50 values between the high- and low-PPRPS groups were statistically analyzed using the Wilcoxon method.Based on the pharmacogenomics database Genomics of Drug Sensitivity in Cancer (GDSC)  was conducted to assess the enrichment scores of our Pan-PCD gene set in every sample we chose. The ssGSEA results are shown in To investigate the biological functions and relevant pathways of these DEGs, GO and KEGG analyses were performed. The top 10 terms for each GO category and the top 30 pathways for KEGG are shown in via univariate Cox regression analysis with p<0.05  and Gene Expression Omnibus (GSE13507). As shown in To further validate the clinical application of our Pan-PCD-related prediction model, we integrated the patients’ clinical information, including grade, stage, age, and PPRPS, to perform univariate and multivariate Cox analyses to develop the nomogram for OS . The results in The heatmap of 15 Pan-PCD genes in the Pan-PCD-related prognostic signature is displayed in + T cells were significantly increased in the high-PPRPS group. However, activated myeloid dendritic cells exhibited a significant decrease in the high-PPRPS group based on CIBERSORT, CIBERSORE-ABS, XCELL, and MCPCOUNTER results. We further analyzed 13 immune-related signatures , kidney renal papillary cell carcinoma (KIRP), and prostate adenocarcinoma (PRAD), but not for kidney chromophobe (KICH) in Cell death has been established as an important anticancer defense mechanism and therapeutic target. Evasion of malignant cells from cell death is regarded as a crucial requirement for malignant transformation and tumorigenesis. In this sense, exploring the mechanisms and functions of cell death, especially the forms of programmed cell death and the steps involved in regulated cell deaths, would shed some light on tumor development and anticancer therapy. Bladder cancer has shown many different PCD-associated signatures that can be used to understand death resistance , prognosIn our study, we utilized Pan-PCD-related DEGs to construct a prognostic signature in bladder cancer. We discovered that bladder cancer exhibited varied Pan-PCD levels based on our TCGA datasets, and these levels were used to create the high-PPRPS group and the low-PPRPS group. The bladder cancer subtypes revealed an intrinsic cell death signature in patients, which subsequently impacted patient prognosis. Accordingly, the high-PPRPS group had a shorter survival time. The Pan-PCD-related prognostic model showed that stage, age, and the PPRPS score were independent prognostic predictors of OS. Specifically, these features were highly associated with a high PPRPS score of Pan-PCD in patients.DEG functional analysis provides some cues on the mechanisms that characterize the high- and low-PPRPS subgroups. GSEA results in subgroups suggested that the expression of genes in the high-PPRPS group is enriched in some classical tumorigenesis-, development- and progression-related pathways. For example, focal adhesion signaling-related genes were enriched in our high-PPRPS group. The signaling in this pathway involves a wide range of prosurvival signaling molecules, including integrins, growth factor receptors, and intracellular molecules, that regulate cell behavior and tumor cell survival . ECMs, sMETTL3, YTHDC1, and YTHDF1 expressions were decreased in the high-PPRPS group, and these genes could potentially serve as candidate drug targets based on pan-PCD subtypes.m6A modifications are increasingly recognized as an important layer of posttranscriptional gene expression regulation. Its dysregulation has been broadly reported within various cancer cells and tumors . Due to Low- and high-PPRPS bladder cancer demonstrated diverse immune landscapes, including immune cell infiltration, immune-related signatures, the tumor microenvironment, and immune checkpoints, based on our analysis. As a result, we hope to identify ideal immunotherapy for high-PPRPS bladder cancer subtypes. We further used the IMvigor210 cohort, a multicenter, 2-cohort, phase 2 trial that investigated the efficacy and safety of atezolizumab in metastatic urothelial carcinoma (mUC), to validate the potential effect of PCDs on bladder cancer. However, the high-PPRPS group showed fewer curative effects than the low-PPRPS group when anti-PD-L1 monoclonal antibody therapy was applied, indicating that patients with these high-PPRPS features will likely not benefit from anti-PD-L1 immunotherapy.50 values for docetaxel, staurosporine, and luminespib. However, patients in the high-PPRPS group were less sensitive to dactolisib, rapamycin, and daporinad. The results may be helpful to guide subsequent therapy for individual patients. The mechanisms by which these three candidate drugs induce Pan-PCD-resistant cells in the high-PPRPS group require further study. One limitation of our study is that our results provide only some clues on the role of PPRPS in bladder cancer. However, the biological functions of Pan-PCD-related DEGs remain unclear, and further in-vitro or in-vivo experiments are required.In the context of cancer treatment, many chemotherapies induce cancer cell death, including apoptosis, ferroptosis, autophagy, and pyroptosis –37. HencWe successfully developed a Pan-PCD-related prognostic signature of bladder cancer to predict a patient’s prognosis and perform risk prediction, and have validated the prognostic model in two other bladder cancer cohorts. Furthermore, the low- and high-PPRPS groups exhibited unique immune landscapes and m6A patterns. Finally, the low-PPRPS group benefited more from anti-PD-L1 immunotherapy, and Pan-PCD subtypes showed diverse sensitivities to chemotherapy. In conclusion, our results demonstrated that the PPRPS facilitates accurate prediction of bladder cancer prognosis and provides a novel classification method to guide the selection of therapeutic treatment.The original contributions presented in the study are included in the article/Conceptualization, MP; Methodology, LZ, MP; Supervision, MP; Validation, LZ, MP; Writing - original draft, LZ; Writing - review & editing, LZ, MP. Both authors contributed to the article and approved the submitted version.This study was supported by the Natural Science Foundation of Hunan Provincial  and the Natural Science Foundation of Changsha City (kq2202389).We appreciated the TCGA, GDSC, and IMVigor210 projects. We also thank American Journal Experts (AJE) for English editing.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.