To solve the instrument loosening problem, we developed a fibroblast growth factor-2-calcium phosphate composite layer as a novel coating material to improve screw fixation strength. The primary aim of the present study was to demonstrate the safety and feasibility of screws coated with the FGF-2-calcium phosphate composite layer for posterior instrumented surgery of the cervical spine. The trial design was a single-arm, open-label, safety and feasibility study. Patients receiving fusion of the cervical spine from C2 (or C3) to C7 (or T1) were recruited. The primary endpoint to confirm safety was any screw-related adverse events. Seven patients who underwent posterior fusion surgery of the cervical spine were enrolled in the present study. The coated pedicle screws were inserted bilaterally into the lowest instrumented vertebrae. There was only one severe adverse event unrelated with the coated screw. Three out of the fourteen coated screws showed loosening. The present results prove the safety and feasibility of pedicle screws coated with the FGF-2-calcium phosphate composite layer for fusion surgery in the cervical spine. This is the first step to apply this novel surface coating in the field of spine surgery. Recent advances in spinal instrumentation have improved clinical outcomes for various kinds of spinal pathologies. However, the increased usage of spinal instrumentation has led to the emergence of spinal instrumentation-specific surgical complications including increased risk of infection ,2,3 instTo solve the instrument loosening problem, several countermeasures have been proposed. A combination with hook/wire  and peneWe developed an apatite basic fibroblast growth factor (Ap-FGF) coating device as a novel material to improve screw fixation strength . It is cThe primary aim of the present study was to demonstrate the safety and feasibility of Ap-FGF-coated screws for posterior instrumented surgery of the cervical spine.https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000030735 (accessed on 1 August 2017)). Inclusion and exclusion criteria are shown in The trial design was a single-arm, open-label, safety and feasibility study. The registration number was UMIN000026771 . bFGF  was dissolved in an over-saturated phosphate–Ca solution  and screws were soaked for 48 h at 37 °C. A specific jig was made to hold the screws within the solution , Ca/P concentration  and bFGF bioassay (NIH 3T3 cell proliferation) were performed. The solution was collected and checked for endotoxins.Eight patients who underwent posterior fusion surgery of the cervical spine were recruited into the present study . IndicatAp-FGF-coated pedicle screws were inserted into the lower instrumented vertebrae. All the patients were followed by assessments of clinical outcomes, X-rays (~1 year after surgery), CT (1 week and 6 months after surgery), and laboratory investigations for 1 year after surgery. The definition of screw loosening was a result of observations of a lucent zone measuring 1 mm or more on the CT scan. Bony union was evaluated by continuity between facet joints on a sagittal reconstruction CT multiplanar image 6 months after surgery or motion of spinous process less than 2 mm in flexion–extension X-ray 1 year after surgery.Adverse events were defined as any symptom or disease observed in a participant after informed consent with or without a causal relationship to the Ap-FGF screw. All adverse-event-related terminology was coded by the investigators according to the ICH International Medical Dictionary for Regulatory Activities, Japanese version (MedDRA/J). Those determinations were performed by an independent data and safety monitoring committee.All procedures used in this study were approved by the institutional review board. Written informed consent was obtained from all patients to participate in this study and for publication. The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.One patient (No. 2) was excluded because of an incomplete procedure of the screw coating process  died from a rupture of an abdominal aneurism six months after surgery. This was considered to have “no relationship with the Ap-FGF screw” .Other adverse events included laboratory data abnormalities, elevation of creatin phospho-kinase (seven cases), liver dysfunction (four cases) and elevation of serum amylase (one case), all of which were considered to have “no relationship with the Ap-FGF-coated screw” . As for p = 0.03). Postoperative VAS arm pain was significantly reduced , although there was no significant difference between pre- and postoperative neck pain .Three out of fourteen Ap-FGF screws showed loosening. One of those was positioned incorrectly, possibly influencing loosening. All loosening was detected with follow-up CT six months after surgery . Bony unThe present trial showed no adverse events associated with the Ap-FGF screws. The only severe adverse event (SAE) was death due to the rupture of an abdominal aortic aneurism. This SAE was considered to have “no relationship with the Ap-FGF-coated screw” because the patient died six months after surgery and a retrospective check of the preoperative CT revealed the aneurism.Abnormalities detected by laboratory analyses were determined as “no relationship with the Ap-FGF-coated screw” because the number and degree of abnormalities was comparable to a standard postoperative course and rapidly resolved without any specific treatment. Therefore, they were possibly influenced by surgical invasiveness and/or drugs used in the perioperative period, including anesthetics, analgesics, and antibiotics, and the incidence of those postoperative laboratory abnormalities were similar in previous patients receiving instrumented fusion surgery of cervical spine. Those determinations were performed by independent data and safety monitoring committee. Previous reports revealed that bFGF is safe for the central nervous system because it had been used safely in laboratory investigations and clinical trials for spinal cord injury and brain infarction ,28. As fOur previous report showed that screw loosening occurred up to 40% of the time at the caudal end of the long cervical fusion construct, possibly because long fusion leads to a longer lever arm . CounterThe present results prove the safety and feasibility of Ap-FGF coating for pedicle screws for fusion surgery in the cervical spine. This is the first step to apply this novel surface coating in the field of spine surgery.


Howevercancers) .Frontiers in Genetics aims to provide an international forum for.1) Bringing together the greatest research efforts in brain-specific molecular/network signature identification by integrating multi-omics/multi-level data;2) Exploring future-generation interesting and practical biomedical applications in AI, machine learning, data sciences, knowledge-based system, etc., to paving the path toward achieving precision medicine in brain disease treatment;3) Addressing the real-world challenges in the fields of AI-based patient stratification and diagnosis by utilizing advanced machine learning or deep learning, and produce a more reliable and promising application environment to develop those technologies.This Research Topic entitled “Advanced Computational Systems Biology Approaches for Accelerating Comprehensive Research of the Human Brain” in Submission for this Research Topic started from May 2022 and closed in October 2022. In nearly 6 months, we received in total 5 paper submissions. All submitted manuscripts had gone through at least three rounds of revision with reviewers in the related fields, including bioinformatics, computational biology, machine learning, and clinical study, etc. The final acceptance rate is 80% with 4 accepted papers in this Research Topic. The summaries of these papers are outlined below.Bao et al. The authors developed a novel two-step GRN inference technique based on the time-delayed correlation coefficient (TDCC) and time-delayed complex-valued S-system model (TDCVSS) to detect the direct associations of GRN more accurately.In the article entitled “Gene Regulatory Identification Based on the Novel Hybrid Time-Delayed Method” by Zhang et al. To demonstrate the key role of ASCL1 gene in the differentiation of neuronal-like glioblastoma (GBM) cancer stem cells, the authors implemented systematic analysis by using Chip-seq data and revealed that EGFR, SPTAN1, and CTNN1B might be the potential down-stream genes of ASCL1 in GBM development, and CTNN1B might make contributions to GBM progression on regulating the cAMP pathway.In the article entitled “Identification of signaling pathways associated with achaete-scute homology 1 in glioblastomas through Chip-seq data bioinformatics” by Yang et al. The authors integrated multiple gene expression datasets from GEO and implemented deep bioinformatics analysis. Finally, they identified 5 signature genes  related to Myocardial infarction (MI).In the article entitled “Bioinformatics analysis to screen for genes related to myocardial infraction” by Chen et al. The authors mainly focused on investigating the morphology and airway volume of oropharynx patients with unilateral complete cleft lip and palate after palatopharyngeal closure. This study reveals that the airway volume, the minimum cross-sectional area of the pharynx, the horizontal cross-sectional area of the hyoid, and the distance between the hard and soft palate tip in patients with complete unilateral cleft lip and palate show significant differences relative to control samples.In the article entitled “The study on the morphological changes of oropharynx in patients with complete unilateral cleft lip and palate after palatopharyngeal closure” by Frontiers in Genetics, as well as all peer-reviewers for their great efforts reviewing the submitted articles, providing constructive suggestions and comments and assisting the editors reaching the final decision. Special thanks will be sent to the Editor-In-Chief (EIC), Enrico Domenici, for their precious time and valuable instructions that help us prepare and finalize this Research Topic.The guest editors would like to thank all the authors submitting their valuable works to this special section of


Deep learning-based computer-aided diagnosis has gained momentum in the radiology field thanks to the technological advances of convolutional neural networks (CNN). However, how to utilize the black-box predictions of these CNN models to the clinical routine still relies on radiologists’ personal judgements. In addition, existing CNN models only improve radiologists’ diagnosis when they outperform the radiologists, thereby limiting their added values for possible efficiency enhancement and improving mostly the diagnostic performances of junior radiologists.p-value < 10−5), reaching about 0.92 over the standalone CNN (~0.87) and senior radiologists (~0.86), and identified a second-order vascularity localization and morphological pattern which was overlooked if only first-order features were considered. We validated the advantages of the integration framework on an already-trained commercial CNN system and our findings using an extra set of ultrasound images of 500 nodules. Our HAIbrid framework allows natural integration to clinical workflow for thyroid nodule malignancy risk stratification and diagnosis, and the proposed GAFM-HAIbrid model may help identify novel diagnosis-relevant second-order features beyond ultrasonography.We present a Human Artificial Intelligence Hybrid (HAIbrid) integrating framework that reweights Thyroid Imaging Reporting and Data System (TIRADS) features and the malignancy score predicted by a convolutional neural network (CNN) for nodule malignancy stratification and diagnosis. We defined extra ultrasonographical features from color Doppler images to explore malignancy-relevant features. We proposed Gated Attentional Factorization Machine (GAFM) to identify second-order interacting features trained via a 10 fold distribution-balanced stratified cross-validation scheme on ultrasound images of 3002 nodules all finally characterized by postoperative pathology , retrospectively collected from 131 hospitals. Our GAFM-HAIbrid model demonstrated significant improvements in Area Under the Curve (AUC) value ( Ultrasound is the most widely used medical imaging tool to evaluate thyroid nodules, whose prevalence is found to be 30% to 68% ,2, and tWith the development of deep learning Convolutional Neural Networks (CNNs), radiologists start to use computer aided diagnosis (CADx) systems as a second opinion for thyroid nodule evaluation ,9,10. ItFor medical image diagnosis, generating class activation heatmaps ,13,14,15+ and listed in In this work, we chose Kwak-TIRADS as the basis for thyroid nodule evaluation as it has been widely adopted in China. In addition, we included extra vasculature-related ultrasound features  that desHypothetically, co-occurrence of features or second-order feature interactions can constituent a unique malignancy-relevant feature. Just as an individual’s inherent inter-dependent preferences over items of certain categories can be modeled by second or higher-order feature interactions using Factorization Machine (FM)  for imprAs a proof of concept, we took a ResNet101 model  pretrainThis study was based on the authorized clinical dataset with continuous data contribution from the consortium of CAAU  with 131For each nodule, ultrasound scans of standard longitudinal and transverse planes were saved, including B-mode and color Doppler images. A retrospective cohort of 3002 thyroid nodules from 3002 patients continuously registered at CAAU alliance hospitals collected between January 2017 and August 2019 following the same protocol as in the previous publication was used for training and cross-validating our proposed model. Of these, 1732 nodules were determined to be benign, and 1270 nodules were malignant according to histopathological diagnosis. These samples were randomly partitioned into 10 folds for cross-validation experiments for which each fold was alternatingly taken as the validation set while the rest were taken as the training set. It is also important to note that dataset shift, which introduces substantial set to set variations, is a known deteriorating factor for accurate performance estimation . To elimData for an additional 500 nodules collected between February and April of 2021 were used to verify results obtained on the former cohort. Half of these nodules were benign and the other half were malignant, confirmed by pathological examinations. This part mainly describes the construction of candidate feature set from features extracted by radiologists and diagnosis results of a convolutional neural network for establishment of interpretable thyroid diagnosis criteria and malignancy risk stratification, as illustrated in The features extracted by radiologists are descriptions of ultrasound images as text data using feature dictionary defined in TIRADS. Each sample is represented by structured data in consistent order. One-Hot Encoding is used to convert text data to feature vectors, using N-bit status registers to encode N states, with each state having an independent register bit, and only one bit being valid at any time. For absent feature description, 0 was used to encode the feature to ensure consistent vector dimension.In our study, the collected samples were labeled on the basis of Kwak-TIRADS and our defined extra features, most of which were already described in the published C-TIRADS  except fThe diagnosis results from CNN-based CADx were included as an additional candidate feature for constructing candidate feature set together with human-extracted features. This is different from the conventional procedure where image features are extracted via a CNN model for later feature fusion and classifications.X.The candidate features were thereafter used to construct weighted second-order feature interactions using either AFM or our proposed variant GAFM module according to the individual contribution of each feature to the diagnosis. The difference between AFM and GAFM is that an additional gate mechanism is introduced to only keep the top-ranked features according to their weights. The inclusion of the gate mechanism is because some insignificant second-order features, if not removed, can interfere the learned weights of other features and return sub-optimal combinations of features for the ultimate thyroid malignancy classifications. The architecture of our proposed GAFM model is illustrated in X and n is the number of the non-zero features. The output of the embedding layer is then the concatenation of multiple embedding vectors as: This layer adopts a sparse representation for input features and embeds each non-zero feature into a dense vector, which can be represented asn vectors, there are n(n-1)/2 interacting vectors, each of which is the element-wise product of two distinct vectors representing their interaction. This can be expressed as:For pairwise interactions of The attention mechanism of the GAFM model is the same as AFM, which parameterizes the attention score with a multi-layer perceptron (MLP). The input of the gate-attention network is the pairwise interacting vectors, while the output is the attention scores, a vector whose dimension is consistent with the number of interacting vectors. The attention score of each feature interaction in the embedding space The gate mechanism introduced in GAFM model sets a gate operation for each second-order interacting feature, and the number of gate operations are consistent with that of the interacting features. When the weight of the interacting feature is greater than the preset threshold, the gate state is open, and second-order interacting feature is retained, otherwise the opposite.We propose a two-step training procedure for our GAFM model. The first step is similar to the training process of an AFM model and there is no gate mechanism involved. After the model converges, we use the gate mechanism to remove minimally relevant second-order interacting features. The second step is to re-train the model after the gate operation with the remaining second-order interacting features and all first-order ones. The output of gate-attention layer can be expressed as:The objective function is the cross-entropy loss function expressed as:j-th element and After the model converges, we normalize the weights of all remaining features through the softmax function, then rank the coefficient of each feature in the model and select the top-ranked features. Following the design principle of Kwak-TIRADS, 15 top-ranked features were selected. The expression of the softmax function is as follows:j:O represents the feature set for sample j that includes all assigned features by radiologists and the diagnosis by the CNN-based CADx system, while i of sample j.Once the feature selection and corresponding weight for each selected feature is determined after the model training, a 1–5 risk stratification system  is constructed. This is performed by summing the weights for each sample i according to the malignancy rate illustrated in the risk stratification module in The malignancy rate for each summed score S  or with a subsequent LR classifier (method 2), or with additionally defined candidate features (method 3), the diagnosis by conventional CADx (method 4), a simple integral approach that combine the diagnoses by radiologists and a CADx system by returning always the higher malignancy (method 5) or a plain integral approach that combines the features defined in TIRADS and the diagnosis results from CADx followed by using LR merely for classification (method 6) or as both a feature selector and classifier (method 7). To elucidate the significance of second-order feature interactions and the importance of further feature weight optimization, we included conventional AFM (method 8), our proposed GAFM variant (method 9) and a conventional method ignoring second-order feature interactions (method 7).TM Thyroid of software version 4.0 (2020) developed by Demetics Medical Technology , was tested to check whether the proposed integration framework could also bring benefits to an independently trained CNN model.For verifying the results obtained from the cross-validation experiments, a CNN-based CADx system, AI-SONICFor cross-validation experiments, we used pairwise two-tailed t-test to evaluate whether the differences in mean AUC values between the GAFM model and control experiments were statistically significant. For comparison of two CNN models integrated through the GAFM-HAIbrid strategy, we subdivided the ultrasound images of 500 nodules to two groups, each of which were further partitioned to five subsets for both intra-group and cross-group statistical comparisons using the feature stratified partition method mentioned above. For intra-group comparisons of different diagnostic methods, as the dataset partitions were kept identical, pairwise two-tail t-tests were used for statistical evaluations. For cross-group comparisons, standard two-tail t-tests were used instead. 0 (where LR was used merely as a classifier without feature exclusion) outperformed each separate method, i.e., Kwak-TIRADS and CADx (+-LR1 improved the diagnosis compared to the case of HAIbrid-LR0 (0.893 ± 0.0017 vs 0.881± 0.0025). Furthermore, AFM-based methods including our proposed variant GAFM achieved significantly better performances  from our nationwide database contributed by 131 member hospitals. From the results, it can be seen that combining the CADx with TIRADS, denoted as HAIbrid+LRand CADx . Interesormances  than theThe resulting TIRADS criteria, referred as HAIbrid-TIRADS which takes diagnosis from CNN-based CADx as an additional feature reweighted together with ultrasonographical features noted by radiologists, are listed in It is worth-noting that our GAFM model identified the second-order feature interaction concerning vasculature localization and morphology .Furthermore, we applied the GAFM-HAIbrid method on two different CNN models to assess the effectiveness of this approach on the test cohort by dividing the ultrasound images of 500 thyroid nodules to two groups of equal sizes in a feature-stratified manner, one for the trained ResNet101 model and the other for a CNN-based CADx system, AI-SONIC margins a and wer margins a,c,d. Thd system a was larFrom the 10-fold cross validation experiments on retrospectively collected thyroid nodule ultrasound images, feature selection and weight reassignment in general can make an influential impact on the performance of the resulted computer-aided TIRADS criteria. For instance, enabling feature selection capability of conventional LR while providing extra candidate features improved the diagnosis compared to the case where LR was only used as a classifier, suggesting the relevance of feature selections on additional features for improving thyroid nodule diagnosis. Furthermore, the score of each selected feature correlated very well with their corresponding odds ratios (ORs), supporting that the learned scores reflect the relative malignancy risks of each feature. Implementing AFM-based feature selection modules especially our proposed GAFM variant within the HAIbrid framework that consider second-order interacting features further improved the diagnostic performances.The GAFM-HAIbrid model identified a second-order vascular-related feature being mainly perinodularly distributed and untwisted. At first glance, it may appear contradictory to the notion that the thyroid nodule malignancy was more associated with the intranodular vascularity given by a study of 402 nodules, in which 23 were malignant . HoweverBased on the 10-fold cross-validation experiments, a first-order feature “punctate echogenic foci of undetermined significance” was also identified by the GAFM-HAIbrid method with an OR of 1.891. Its OR was different from the OR of 0.944 in the original C-TIRADS paper, where it was considered insignificant . This isTM Thyroid system was largely closed-off. This suggests that standardizing the incorporation of radiologists’ expertise to CNN-based CADx systems may outweigh the improvement of standalone CADx systems. In contrast, by inspecting the developments of high-profile deep learning algorithms from a historical perspective, it can be seen that they typically outperformed the previous state of the art algorithms by 1–3% [TM Thyroid system than the ResNet101 model may have benefited more from much larger available training samples than we had in this study. Nevertheless, this indicates that from a practical perspective, pushing the performance of a standalone CADx system to exceed senior radiologists’ diagnostic performance for the real-world clinical workflow may no longer be an urgent need.It is also interesting to note that our test dataset results show that combining radiologists’ diagnoses through our HAIbrid approach had a greater impact on the under-performing ResNet such that the standalone performance gap compared to AI-SONIC by 1–3% ,30,31,32At the same time, the results show that our HAIbrid approach did not require the CNN-based CADx to be superior to radiologists for diagnosis performance improvement. This is different from other publications where the improvement of radiologists’ diagnosis by consulting the results from CADx systems demands these systems to be more accurate than the radiologists ,33. Our It is however desirable to relieve the burden of radiologists as much as possible. It is preferable to obtain the TIRADS features from another CNN system as done in reference  and to aTo conclude, our HAIbrid approach allows integration of CNNs of arbitrary architectural designs, combines thyroid nodule diagnosis results from CNN-based CADx system and radiologist-defined features, permits the establishment of novel human interpretable TIRADS criteria that outperform the original diagnostic methods and requires no extra efforts from radiologists to adapt and integrate to their clinical workflow. Our proposed GAFM feature selection method enables the identification of clinically relevant second-order feature interactions, which have been overlooked by radiologists and conventional feature selection methods. We anticipate that our integrated approach can be generally applicable for medical imaging-based diagnosis of other diseases beyond ultrasonography as long as radiologists may consult the second opinion from a CNN-based CADx system and our proposed GAFM model can be presumably adopted to identify potentially important second-order feature interactions that are overlooked in existing diagnostic criteria.A patent application has been filed with publication number CN113889229A, and publication date 24 January 2022.


The “Cooperative Model Framework” demonstrates the efficacy of this approach by assessing the synthetically generated data.This paper describes and provides the data on the regenerated-impedance spectra that is computed from experimental results of electrochemical impedance spectroscopy measurements taken from a commercial Li-ion battery. The empirical impedance data of secondary coin type Li-ion batteries were collected in different states of charge ranging from empty to full state of charge configurations. This approach utilizes only a small seed ( EISElectrochemical impedance spectroscopydcVPotential measured at direct currentdcICurrent measured at direct currentffrequencyphzZPhase angle of impedanceMLMachine learningSoCState of chargeLIRLithium-ion rechargeableknnK-nearest neighbormonmlpMonotone multi-layer perceptronsvmRadialRadial support vector machinegcvEarthMultivariate adaptive regression splines with generalized cross validationglmGeneralized linear modelpprProjection pursuit regressionrpartRecursive partitioning and regression treerfRandom forestxgbExtreme gradient boostingDartDropouts meet multiple additive regression treegaussprGauss processRMSERoot mean square errorRMSESDRoot mean square error standard deviationrZReal part of complex impedancejZImaginary part of complex impedancedcDirect currentacAlternating currentSpecifications Table•Experimental impedance data taken in particular state of charge (SoC) conditions were used to build a weighted ensemble of disparate models selected from performance and non-correlative criteria.•The approach is called “The Cooperative Model Framework” (or co-modeling) produce synthetic impedance data from minimal experimental data training.•The synthetic data can be used on battery management systems in order to monitor the performance of Li-ion batteries.•The synthetic data can be used to study on the analysis of new battery designs.1The data described in this article were the results of the combination of experimental and machine learning (ML) methods. The experimental impedance data on Li-ion batteries were collected by using electrochemical impedance spectroscopy under different charging conditions. The computational data were obtained by using a novel data-centric machine learning approach to build an ensemble of models to effectively complete the experimental results. The amount of experimental data were intentionally fixed in small volume in order to observe the productiveness of the co-modeling approach with the minimum amount of input.Mendeley Data) include the excitation potential (Vdc) and frequency (f) as inputs, and corresponding current (Idc) and phase angle of impedance (Zphz) as outputs along with the resulting real (Zr) and imaginary (Zj) components of battery impedance, and these components can be used in Nyquist plotting.The impedance data is useful for analyzing and monitoring the characteristics and performance of rechargeable Li-ion batteries. Battery impedance can be represented either by Nyquist or Bode Format according to the purpose of analysis. The empirical data in this article consist of the parameters and results of the offline potentiostatic impedance measurements taken from commercial secondary LIR2032 Li-ion battery cells under different cell potentials from 3.2V to 4.2V. The datasets  is included in the same data repository.Phase angle of impedance as a function of applied frequency is one of the representations of impedance response of an electrochemical system; and it is designated as the Bode plotting. An equivalent electrical circuit is a useful illustration of an electrochemical system with electrical components in a circuit that provides information about charge and mass transport occurring in the system. The phase angle of impedance for any component in the equivalent electrical circuit corresponding to the electrochemical system is the phase shift between the applied excitation potential and current passing through that component. A novel ML approach (co-modelling approach) is used to process the empirical impedance data in order to regenerate the phase angle of impedance 2Electrochemical Impedance Spectroscopy (EIS) experiments were performed on commercial coin type Li-ion batteries (LIR2032) using Gamry REF3000AE potentiostat. EIS measurements were taken at different SoC by applying 10 mV perturbation potential between the frequency range of 100 kHz and 10 mHz. SoC is a function of open circuit cell potential of the batteries such that it can be varied by changing the potential of the batteries. A potentiostat can both supply direct or alternating current to the system that is analyzed. The potentiostat provided direct current (dc) to change the cell potential; on the other hand, an alternating current (ac) is applied to measure the impedance at a specific SoC for the batteries. The results of EIS measurements were used to build the co-model. phz and Idc cooperative models are given in The details of our ZMendeley Data.The datasets are available on https://github.com/hasankurban/Machine-Learning-Based-Regeneration-of-Li-ion-Battery-Impedance.Code, ML models and ML regenerated impedance are accessible at: This work does not contain any human studies or animal experiments. The data were not collected using social media platforms. The authors declare that they have followed the general ethics rules for scientific research and publishing.Selcuk Temiz: Conceptualization, Methodology, Writing – original draft preparation, Investigation; Hasan Kurban: Conceptualization, Methodology, Writing – original draft preparation, Data curation, Applying Machine Learning algorithms; Salim Erol: Conceptualization, Methodology, Writing – original draft preparation, Visualization, Investigation; Mehmet M. Dalkilic: Conceptualization, Methodology, Applying Machine Learning algorithms, Writing – review & editing, Supervision.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


In this paper, we propose a novel interference alignment (IA) technique for an in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) cellular network where a base station (BS) and user equipment (UE) are equipped with multiple antennas, and the local channel state information (CSI) is available at all nodes. Considering a practical IBFD MIMO cellular network, it is assumed that only the BS operates with full-duplex (FD) communication while UE operate in half-duplex (HD) mode. These IBFD networks introduce a new type of interference called cross-link interference (CLI), in which uplink UE affects downlink UE. The proposed IA technique consists of two symmetric IA schemes according to the number of antennas in the uplink and downlink UE, and both schemes effectively mitigate CLI in the IBFD MIMO network. It is worth noting that both IA schemes are adaptively applicable according to the network’s quality-of-service (QoS) requirements, such as uplink and downlink traffic demands. Furthermore, we theoretically characterize and prove the achievable sum-degrees-of-freedom (DoF) of the proposed IA technique. Simulation results show that the proposed IA technique significantly improves the sum rate performance compared to conventional HD communications (multi-user MIMO) while achieving the same achievable DoF as the interference-free IBFD MIMO network. Next-generation cellular networks require significantly higher data rates and spectral efficiencies than modern commercial mobile communication systems to accommodate the surging traffic demands. Recently, in-band full-duplex (IBFD) communication has emerged as one of the promising technologies to fulfill these quality-of-service (QoS) requirements in sixth-generation 6G) wireless communication systems ,2. CompaG wirelesIn practical cellular networks, the FD operation may only be supported by the base station (BS) because it is nontrivial to implement on the user equipment (UE) due to the extra hardware burden ,14. In tSeveral interference management techniques against the CLI have been recently studied within the context of exploiting interference alignment (IA) and a degrees-of-freedom (DoF) optimal approach . InterfeTo make IA more implementable, different types of IA have been studied. In , a one-sfeasibility condition of IA [To completely eliminate the CLI in an IBFD MIMO network, it is necessary to take the appropriate number of equipped antennas for each node, also called the on of IA . We defiWe present two IA schemes based on the distributed manner that can alleviate the signaling overhead caused by CSI sharing between nodes ,34. MoreWe theoretically characterize and prove the achievable DoF of the proposed IA schemes and show that they achieve the same DoF as the interference-free IBFD MIMO network.In this paper, we propose a novel IA technique operating under local CSI to mitigate the CLI in general IBFD MIMO networks with FD BS and HD UE. In summary, our main contributions to this paper are as follows:It is also worth noting that the proposed two IA schemes can be adaptively applied according to uplink and downlink QoS requirements, such as traffic demands.The remainder of this paper is organized as follows. In M each for transmission and reception . In other words, the BS simultaneously transmits and receives data over the same frequency, but the UE either transmits (uplink) or receives (downlink) data with the same radio resource. Recently, a dual-separated antenna architecture for IBFD radios has been proposed, which enables the BS to operate FD communication by isolating transmit and receive antenna panels [cross-link interference (CLI).We consider an in-band full-duplex (IBFD) MIMO cellular network consisting of a base station (BS) with a panels ,36. It ia panels ,31. The plink UE ,35. Becajth uplink UE to the ith downlink UE. Each element of all channel matrices: ith downlink UE is assumed to know its jth uplink UE is assumed to know its local CSI.Let property . Note thith downlink UE, denoted by jth uplink UE, respectively. We assume that each uplink UE sends a single data stream and each downlink UE also receives a single data stream; ith downlink UE that follows an i.i.d. ith downlink UE applies its receive beamforming vector defined as The  uid∈CLd× to the rMeanwhile, the received signal vector at the BS, denoted by We will present in n block codes and its achievable DoF [Encoding: The encoding function of the BS is given by jth uplink UE is given by Decoding: Upon receiving signal vectors from ith downlink UE is given by Let us define a set of length able DoF ,35. The able DoF . Supposiachievable rate for the IBFD cellular network if there exists a code sequence of n increases for all ith downlink UE and the jth uplink UE, respectively, and A tuple stem SNR . The DoFWe first summarize the main result of this paper in terms of the achievable sum-DoF and then elaborate on the overall procedure of the proposed IA schemes for achieving this DoF.Consider the IBFD MIMO network described in Theorem 1.The following DoF is achievable in the IBFD MIMO network via the proposed IA techniqueProof. We refer to Remark 1.The DoF of the conventional HD MIMO network is given by M, and thus the proposed technique achieves For the first achievable scheme, we assume that ved from  as a spejth uplink UE is designed byjth uplink UE at the BS. In fact, In the first achievable scheme, transmit beamforming vectors at the uplink UE are preferentially designed. By exploiting local CSI, the transmit beamforming vector of the Each uplink UE feeds its transmit beamforming vector back to the BS so that the BS decorrelates multiple uplink signals from the uplink UE. The BS then obtains effective channel vectors from the uplink UE to itself, denoted byith downlink UE also obtains effective channel vectors between itself and the uplink UE, At this time, we assume that the ith downlink UE considering transmit beamforming vectors of the uplink UE. It is worth noting that such a vector Next, to cope with both the CLI from the uplink UE and the inter-stream interference  from the BS, receive beamforming vectors are designed at the downlink UE; each is chosen asuid=u∈NulEach downlink UE feeds its receive beamforming vector back to the BS for multiplexing multiple downlink signals at the BS. Then, the BS obtains effective channel vectors from itself to the downlink UE, denoted byThe BS needs a pre-coding matrix for decorrelating multiple spatial streams to the downlink UE. Recall that we assume ctors in  as follol stream .The BS also needs a post-coding matrix ctors in , this isFor the second achievable scheme, we assume that ith downlink UE is designed byith downlink UE. In fact, In the second achievable scheme, receive beamforming vectors at the downlink UE are preferentially designed, while the transmit beamforming at the uplink UE is designed prior to the receive beamforming at the downlink UE in the first achievable scheme in jth uplink UE also obtains effective channel vectors between itself and the downlink UE, As in gid in  and the jth uplink UE is chosen asjth uplink UE to The transmit beamforming vector of the hosen asvju=v∈NulAs in gju in . On the The BS designs pre- and post-coding matrices, rices in  and 14)VBSd and ith downlink UE and Applying the receive beamforming in  for Ld≥LLd≥Lu or  for Ld≤Ld signal  can be rAfter post-coding in  for Ld≥Ld≥Lu and  for Ld≤Ld signal  is given signal ηM, and in the second achievable scheme, we assume that In the first achievable scheme, we assume that jth uplink UE is given byjth element of From , the achHence, the achievable DoF of the uplink is given from  by(26)ηFinally, the achievable sum-DoF of the proposed IA technique in the IBFD MIMO cellular network is given byFor the first achievable scheme  communication is one of the promising technologies for next-generation cellular networks. In this paper, we have investigated a practical IBFD MIMO cellular network in which a BS operates full-duplex (FD) communication and user equipment (UE) communicates in half-duplex (HD) mode. These IBFD networks introduce a new interference source called cross-link interference (CLI). We proposed a novel distributed interference alignment (IA) technique to alleviate the CLI. Briefly, the proposed IA technique consists of two achievable schemes: the


Arabidopsis protein interaction datasets better than the previously used methods. We show that Ollivier-Ricci curvature with side information identified an expanded auxin community to include an important protein stability complex, the Cop9 signalosome, consistent with previous reported links to auxin response and root development. The results show that community detection based on Ollivier-Ricci curvature with side information can uncover novel components and novel communities in biological networks, providing novel insight into the organization and function of complex networks.Cellular biological networks represent the molecular interactions that shape function of living cells. Uncovering the organization of a biological network requires efficient and accurate algorithms to determine the components, termed communities, underlying specific processes. Detecting functional communities is challenging because reconstructed biological networks are always incomplete due to technical bias and biological complexity, and the evaluation of putative communities is further complicated by a lack of known ground truth. To address these challenges, we developed a geometric-based detection framework based on Ollivier-Ricci curvature to exploit information about network topology to perform community detection from partially observed biological networks. We further improved this approach by integrating knowledge of gene function, termed side information, into the Ollivier-Ricci curvature algorithm to aid in community detection. This approach identified essential conserved and varied biological communities from partially observed  Such cellular biological networks represent biophysical snapshots of a global organization of cellular components. The maps of molecular interactions are often represented as networks, where nodes corresponding to cellular components are connected by edges representing either physical or functional interactions determined from the empirical interaction data4. A central hypothesis to biological network analysis is that highly connected nodes represent organized units, so called communities in network science, that conduct one or more biological functions. The level of functional organization can occur across scales, ranging from discrete motifs to larger order modules5. Conceptually, a motif represents the lowest functional organization, such that highly connected nodes perform a discrete function, while interacting motifs form modules that perform higher order cellular functions6.A key challenge in systems biology is understanding how individual molecular components interact to form functional communities giving rise to cell structure and function. Uncovering the organizing principles that determine these interactions is crucial for developing a systematic understanding of molecular functions of pathways and their crosstalk. One approach is to map the physical or functional interactions between cellular components, including DNA, RNA, proteins and small molecules, to construct a cellular biological network7 iteratively removes the edge with the largest edge betweenness, a measure of the number of shortest paths passing through an edge, in a graph. Modularity-based community detection10 measures the quality of the division of the network into densely connected modules/communities. Although there are other community detection methods, i.e., spin model-based11 and random walk-based12 methods, the community detection for biological networks faces several challenges: (i) the high-dimensionality, complex multi-scale dynamics and interdependence among biological constituents renders current techniques as either inaccurate or provide incomplete understanding; (ii) community detection algorithms commonly applied to biological networks arose from the information theory and assume complete network information . This is rarely if ever true for biological datasets due to biological data acquisition conditions, such as specific developmental stages and growth conditions, and/or technological limitations. Consequently, only a partial snapshot of a complete molecular interaction network is available for data analysis, which may result in the missing nodes and/or node connections in a pathway15; (iii) related to network completeness, there is a trade-off between data quality and throughput, where efforts to capture more of a network’s nodes can suffer from higher false-positives, which will negatively impact community detection18; (iv) Current mathematical approaches do not integrate known biological node information during community detection. Known information is often used post-hoc to help identify community function, but the approach is often subjective and lacks a robust framework, failing to utilize the prior knowledge on biological functions of genes and pathways.Various community detection algorithms have been proposed to decompose complicated large-scale networks to infer their underlying organization and identify communities with shared functions. For instance, the Girvan–Newman (GN) algorithm19 (Ollivier-Ricci20 and Forman-Ricci21) have been applied in the study of networks. Earlier studies22 described the topological implications of curvature, particularly negative curvature, on the higher-order connectivity and the existence of central, influential neighborhoods in biological and social networks. Recent work using network Ollivier-Ricci curvature include the analysis of the internet topology23, quantifying the systemic risk and fragility of financial systems24, as well as cancer25, brain26, and drug-drug interaction27 networks and machine learning for biological applications28. The Forman-Ricci curvature has also been applied to the analysis of biological networks and its structures30. Additionally, the Ollivier-Ricci curvature has been applied as a tool for network community detection utilizing the implications of negative curvature27 and Ricci flow31. While conventional community detection algorithms rely on network structure alone, they ignore available valuable metadata, sometimes termed nodal attributes. Previous work extended the Stochastic Block Model to incorporate covariates or extra relevant information in network analysis33, and others incorporate nodal attributes as part of the community detection procedure38. Some of these not only allow community detection while considering additional nodal information, but are also able to generate networks with communities correlated with node attributes or deal with missing data40.The applications of geometric analysis of networks have increased in the field of network science. Understanding the underlying topology of a network is important in revealing the salient properties of large-scale complex networks. One of the geometric network measures is the concept of network curvature. Ricci curvature and particularly its discretized forms27. In addition to this novel algorithmic approach to community detection, our approach advances community detection by incorporating prior knowledge of node-level function annotation, so called side information (SI). Side information is inherently sparse for biological data, where most genes have an unknown function, but uses high-confidence functional annotation as ground-truth information for community function. We applied the ORC-based community detection coupled with side information approach on both synthetic and real-world protein-protein interaction (PPI) networks collected from various Arabidopsis thaliana experiments and evaluated the performance by comparing the functions of the detected communities with node-level ground-truth functions. The results demonstrate geometric topology and side information can be exploited to identify known functional communities, identify novel members of known and novel communities to understand complex biological networks.To further address the challenge of community detection in biological networks, we propose the Ollivier-Ricci curvature (ORC)-based community identification (ORCCI) coupled with side information to identify functional communities from graph representations of biological interaction data. Using this framework, we quantify the network geometric topology and incorporate prior knowledge about nodes into the community detection algorithm Fig. . This OR41. The synthetic networks contained 1000 nodes belonging to 10 pre-defined ground-truth communities  is a fine-grained final partition of the network where all the negative curvature edges have been removed; and ORC-maximum modularity (denoted as ORC MM) is an intermediary partition of the network where the network modularity measure is maximized. As the ORC MM identifies communities prior to their terminal split, it results in merged and larger communities compared to ORC.To develop the geometric topology-based ORC community detection algorithm, we modified the ORC algorithm to include side information as a constraint during edge removal. Here, an edge that would normally have been removed, would be retained between two nodes if they shared the same side information. Our rationale was that adding known node information into biological network analysis would allow us to leverage prior experimental information and assist community detection. We analyzed the performance using synthetic networks constructed with the Stochastic Block Model (SBM)ies Fig. a. The co42. For the ORC  partition, we found that increased network observability resulted in more accurate community detection in synthetic networks with a fixed amount of side information  to evaluate ORC-based community detection performance on the synthetic networksORC MM community partition. Similarly, increasing network observability and side information lead to more accurate community detection , performed and benchmarked the results versus an edge betweenness-based7 community detection algorithm previously applied to the 47. From the four ORC-based community detection approaches, we identified 18–30 potential functional communities from 45 and Gene Ontology (GO) enrichment analysis46   and modules 5. We found that the control edge-betweenness method led to fewer small communities (size ORC and ORC+SI) identified a large proportion of small communities and motifs  compared to the ORC final partitions   into several modules with distinct functions (phyto-single)  of a specific module . However, ORC MM+SI had lower performance compared to ORC MM. The seemingly reduced performance when side-information was added to ORC MM was attributed to the way KEGG/GO assigns multiple functions to large communities inflating the performance score. With side information, this has led to more smaller communities with dedicated functions  to the full phytohormone interactome dataset, termed 47. The ORC+SI, ORC MM+SI) show a higher average pathway protein ratio on the ORC+SI identified less motifs (53) and modules (33) in the ORC method  which is a similar observation in ORC MM breakdown the largest communities, we did not find more single-function modules identified by ORC MM+SI than ORC MM, which was different from the ORC MM+SI performance on ORC MM+SI may be due to the increased network size and number of interactions among proteins in ORC+SI detects more biological meaningful modules than the other three ORC-based methods, including 19 modules with phytohormone functions (phyto-single and phyto-multi) and 14 modules with other functions, such as gene regulation, protein processing, and RNA processing  and modules  ratio as the number of overlapping proteins in communities identified both by ORC-based methods and the edge-clustering method , auxin-2 (top-right), auxin-3 (top-left), and auxin-4 (bottom-left) 56 , provided crucial side information bridging auxin-2 with auxin-1 and auxin-3. This illustrates how side information can impact community detection.We hypothesized that the varied protein members uniquely belonging to an ORC community may contain novel components and relationships functioning in the pathway. An important application of community detection is to identify such novel components and relationships within known pathways, discover potential functional pathways, and reveal unknown interactions between pathways. To test our hypothesis and evaluate whether side information can assist ORC-based community detection to identify novel components and relationships in the whole-genome mentclass2pt{minimORC Fig. f,i. Baseft) Fig. f. Auxin-ORC+SI was enriched for auxin function  involved in phosphorelay signal transduction acting upstream or within cytokinin-activated signaling pathway but without experimental validation65. Taken together, the use of side information helped identify potentially novel components in the auxin response pathway, linking to other possible functions and the cytokinin pathway. Future research to validate and explore these connections is needed.To determine if this expanded auxin community is functionally relevant, GO enrichment analysis revealed that the community identified by 54. The ORC+SI provided better community detection in ORC+SI identified three phytohormone communities for comparison of the variation of protein members and local network structures  in the Similarly, partial observation caused dramatic community structure variation of the other two phytohormone communities, GA/JA and BR signaling communities, across the three datasets. Compared with IN Figs. , S5. Fories Fig. a,b,d1. Cets Fig. c,d. For Biological systems are complex because they contain many individual components that are interconnected at different organizational scales. At the scale of cells, genes can be represented as biological networks  for the purpose of understanding the organization, structure and collective gene function for biological processes. However, complete biological network information is seldom available due to biological and technical limitations. Hence, partial network observation poses a problem in downstream community detection analysis where basic network science algorithms assume complete network information. Problems related to observability are not easily overcome, as they relate to technical limitations encountered when balancing high-throughput, large-scale, and accurate data collection of biological systems. To mitigate this limitation, we propose that using a subset of extensively studied proteins, whose biological function is documented, to guide community detection, we can still identify biologically functional communities from partially observed networks. Here, we introduced geometric topology-based network analysis for community detection and addressed the challenge of missing observations by incorporating nodal side information to improve the community detection performance.66. In this work, we exploited the ORC-based community detection algorithm, which iteratively divides the network into communities by removing the edge with the most negative curvature based on the hypothesis that negative edge curvatures act as bridges between functional communities27. We further guided community detection by incorporating biological information in the form of functional gene annotation  to assist in edge removal criteria. We evaluated the community detection performance based on two ORC-based network community partitions: ORC final partition (ORC), and maximum modularity partition (ORC MM). From implementation, the ORC partition results in the finest-grained community partition while the ORC MM results in merged and larger communities. Synthetic network results without the aid of side information showed that ORC performed better at lower network observability  with V denoting the set of nodes and E denoting the set of edges. The network size is S, with S and evaluate the ORCCI performance. We test this for We generated the synthetic networks using the Stochastic Block Model (SBM), which is a generative model for random graphs with planted community structuresFor the synthetic network experiment, we ran the community detection on an SBM model of 1000 nodes with 10 pre-defined ground truth communities of varying sizes . Figure 76 to graphs or networks77. The notion of curvature is a measure of the amount by which a geometric object deviates from being flat (Euclidean plane). The idea of Ricci curvature, on the other hand, is a notion of curvature to a discrete triangulated surface (coarse geometry) or graphs. In the graph/network context, the ball around x is the set of neighbors of x (same for y). Similarly, the idea is to find the optimal way to transfer the ball of mass from the vertex x to y.The proposed community detection algorithm utilizes the coarse geometry topological concept of the Ollivier-Ricci curvatureAlgorithm 1 shows the implementation of the proposed community detection augmented with side information. The main idea is the recursive removal of the most negatively curved edge in the network while keeping in mind not to remove the “known” edges based on the a priori side information. Note that this a priori side information is assumed to be carefully curated from high-confidence functional annotation from prior literature. The algorithm performance will be limited if the side information is not correlated with the hidden community structure.78 was shown to be super-cubic. Interior-point or Orlin’s algorithms have complexity of V as the total number of vertices in the Wasserstein distance sub-problem80  via the wavelet EMD approximation leading to an overall time complexity of The time complexity of the proposed ORC-based community detection algorithm boils down to the calculation of the edge ORC of the network. The time complexity to compute the ORC for each edge is essentially the Wasserstein distance computation complexity based on linear programming. Practical run time complexity using network (transportation) simplex algorithmArabidopsis thaliana (Arabidopsis)47. Arabidopsis, as a model organism in plant biology, has a large number of genes within its genome that are functionally identified and characterized by classical molecular and genetic approaches. For example, several databases such as TAIR are available with gene functional annotation and several of mutation lines uncovering the genotype-phenotype relationships. This makes it a gold-standard platform to explore the biological networks82.We apply the ORCCI-based community detection methods to the real-world biological protein networks to discover functional motifs and modules. This can allow us to better understand the protein dynamics and evolution and potentially discover novel insights. We choose three publicly available protein interaction networks that map the pairwise physical associations between proteins in the chosen model plant 47  is the genome-wide protein network that allows us to observe the local networks and generate systems-level hypothesis  the datasets share a core set of proteins that are involved in phytohormone signaling associated pathways, and (b) the datasets vary in network sizes. For example, the Arabidopsis phytohormone interactome main  and maximum modularity partition (ORC MM), and the baseline method, the betweenness centrality method (Btwns) used in Ref.45 and Database for Annotation, Visualization and Integrated Discovery (DAVID)52, gene ontology enrichment analysis53, and gene description analysis.In contrast to the ground-truth data used as gold standards for verifying the community detection in the synthetic networks, there is rarely a straightforward ground-truth for biological networks or modules. To evaluate the performance of different community detection methods on the protein–protein network, we collected the meta-data for individual proteins that involve in eight phytohormone pathways. We considered several compensate gold standards derived from the gene set analysis, including the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysisSupplementary Information.Supplementary Table 1.Supplementary Table 2.Supplementary Table 3.Supplementary Table 4.Supplementary Table 5.Supplementary Table 6.


This study aims to improve dementia literacy and competence to use music in practice with people with dementia among students in health professional fields. The eight-week curriculum was developed by a gerontology social worker and a subject matter expert on personalized music use for people with dementia. Two focus groups were completed in Spring of 2022 with people living with dementia and care partners to refine the curriculum and include information that those with lived experience felt was important for future health care professionals to know. The study used 2 single group designed cohorts of students who received the 8-week educational intervention over Zoom. Each cohort included 2 persons living with dementia (PWD) as co-trainers. Pre- and post- surveys included a modified Alzheimer’s Disease Knowledge Scale and Dementia Attitude Scale. Participants (n=17) included Social Work = 8, Nursing = 2, Psychology =3, and Others =4. Total of 11 student participants completed both pre-test and post-test surveys. Paired t-tests were used to compare pre-post differences. At post-test, participants reported increased dementia knowledge ; increased dementia attitudes ; and improved competency on using music with PWD compared to the baseline scores. The 8-week intervention showed a statistically positive impact on dementia attitudes and competency of music use. The findings of this study laid the groundwork for future studies on training current service professionals and comparing their practice after the training to non-trained professionals to measure the impact of the training in intervention.


The effect of transplantation of bone-marrow mononuclear cells (BM-MNCs) and mesenchymal stem cells (MSCs) on ejection fraction (LVEF) has been studied in patients with acute myocardial infarction (AMI) in clinical trials. This raises the question that which type of cell may help improve LVEF better in AMI patients. No meta-analysis of clinical trials has yet addressed this question.Electronic databases were searched thoroughly to find eligible trials on the effects of transplantation of BM-MNCs and MSCs in patients with AMI. The primary outcome was improvement in LVEF. Data were synthesized using random-effects meta-analysis. For maximizing the credibility of subgroup analysis, we used the instrument for assessing the Credibility of Effect Modification of Analyses (ICEMAN) for meta-analyses.p < 0.001; MSCs: WMD = 3.71%, 95% CI = 2.32 to 5.09, p < 0.001), and according to ICEMAN criteria, MSCs are more effective. For selected population of patients who received stem cell transplantation in early course after AMI (less than 11 days), this effect was even more pronounced .A total of 36 trials (26 on BM-MNCs and 10 on MSCs) with 2489 patients (1466 were transplanted [1241 with BM-MNCs and 225 with MSCs] and 1023 as controls) were included. Both types of cells showed significant improvements in ejection fraction in short-term follow-up (BM-MNCs: WMD = 2.13%, 95% CI = 1.23 to 3.04, Our results showed that transplantation of MSCs after AMI might increase LVEF more than BM-MNCs; also, based on ICEMAN, there was likely effect modification between subgroups although uncertainty still remained.The online version contains supplementary material available at 10.1186/s13287-022-02883-3. Inadequate blood flow and oxygen supply secondary to formation of thrombus in coronary arteries activate a series of complications leading to myocardial injury, leading to ventricular failure. It is noteworthy that the repair mechanisms following reperfusion in the setting of acute myocardial infarction (AMI) causes irreversible damage to the myocardium by releasing free radicals . On top It has been shown that cell therapy of the infarcted myocardium can promote regeneration of the cardiomyocytes and angiogenic capacity by producing different paracrine factors . Among dThe protocol of this systematic review and meta-analysis was previously registered in PROSPERO (CRD42022296966) and it was synthesized and reported using the methodology recommended by the Cochrane Handbook for Systematic Reviews of Interventions .The potential eligible studies were parallel group controlled clinical trials.All the patients diagnosed with STEMI regardless of age, sex, and baseline echocardiographic indices.Trials which enrolled the patients with STEMI that were treated with successful primary percutaneous coronary intervention (PCI) and stent implantation or thrombolytics and also those that assigned the participants into a group of intervention which received an injection of either MSCs or BM-MNCs with any delivery route and a control arm which received standard therapy with or without placebo injection were considered for eligibility.Changes in the main echocardiographic indices from baseline including LVEF, left ventricular end-diastolic volume (LVEDV), and left ventricular end-systolic volume (LVESV) were selected as the primary outcome measures of interest. The required follow-up period for measuring the change from baseline values was 4–6 months after the primary measurement of the indices.Hospitalization due to congestive heart failure (CHF) at the longest duration of follow-up was listed as the secondary outcome.We searched PubMed, Embase, Web of Science, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) to find the relevant English trials using a combination of keywords and controlled vocabulary such as Medical Subject Headings (MeSH). The last search was run on January 10th, 2022, and we applied no restrictions on the time frame. We used the following keywords for this search: “stem cell,” “bone marrow,” “mononuclear cell,” “mesenchymal cell,” myocardial infarction,” and “acute myocardial infarction.” Handsearching of the potentially eligible studies was done for finding other relevant articles.After developing the search strategy, two reviewers (AH and AA) independently screened the abstracts or/and titles of the retrieved records following the removal of duplicate records. We excluded the clearly irrelevant results falling out of the eligibility criteria for this review. Then, the reviewers screened the full text of the remaining articles for final assessment to identify the eligible studies which were in accordance with our pre-specified inclusion and exclusion criteria. In case of any discrepancies, disagreements were resolved through discussion between the two authors. For the present systematic review, we included all the controlled clinical trials which had performed transplantation of either BM-MNCs or MSCs in patients diagnosed with acute myocardial infarction following successful PCI and stent implantation or thrombolytic therapy and compared them to a control arm of acute MI patients treated with standard therapy with or without injection of placebo. The potentially eligible studies were the ones measuring baseline and final values of primary outcomes  and the absolute change of final measures from the baseline. A PRISMA flow diagram illustrating the selection process is presented in Fig. Two review authors (AH and AA) independently extracted the information and transferred the data to the pre-specified form in Microsoft Excel Spreadsheet Software. The accuracy and consistency of the information was rechecked by both authors and disagreements on data extraction were resolved by discussion between the reviewers. The following information was extracted: characteristics of the included studies , general participant details (baseline demographics and sample size of the intervention and control groups), intervention details , echocardiographic indices  of LVEF, LVEDV, and LVESV), the imaging modality used for echocardiographic indices, and major adverse cardiovascular events .The quality appraisal of eligible studies was done by a single author (AH) and rechecked by a second reviewer (AA), using the Cochrane Collaboration’s tool for assessing the risk of bias in randomized trials. The indicators used for risk of bias included selection, performance, detection, attrition, and reporting bias. We reported the risk of bias with Review Manager (RevMan 5.1.7) Software and rated the status of bias in each category as low, unclear, or high risk. If there were any disagreements, we resolved them with discussion.I2 and the Cochran’s Q test were used. We performed influence analysis to assess the potential effect of each study on the final results. We carried out all the analyses using Stata software version 13 . Pooled effects with confidence intervals that did not cross the zero line were considered as statistically significant.For our main analysis on echocardiographic indices , we expressed continuous data as weighted mean difference (WMD) and 95% confidence interval (95% CI) using the DerSimonian and Laird method  with ranWe conducted a subgroup analysis in this meta-analysis. The eligible trials investigated transplantation of two main lineages of the stem cells (BM-MNCs vs MSCs) for acute MI patients. Thus, we grouped the studies based on the type of cells administered (BM-MNCs group vs. MSCs group) and performed the subgroup analyses on all the outcomes (echocardiographic indices and decompensated heart failure events) to see if there is any significant difference between the two types of cells. To observe the results of studies with more validated method, we conducted a sensitivity analysis; we excluded the studies in which the cells were administered after 11 days after acute MI (injection time ≤ 10 days), the cells were delivered via methods other than intracoronary injection, and the modality used for measuring ventricular indices  was other than echocardiography. For interpretation of potential subgroup effects , we employed the instrument for assessing the Credibility of Effect Modification of Analyses (ICEMAN) for meta-analyses . This quFor this systematic review, preliminary search yielded 3192 records from electronic databases and after removal of 732 duplicate records, abstracts and titles of the remaining ones were screened for eligibility. After full-text screening of 198 studies, 161 articles failed to meet all the inclusion criteria or lacked adequate statistical information. We finally included a total of 36 trials . All the trials were parallel-group randomized controlled designed except one study  on MSCs A total of 2489 patients diagnosed with STEMI were included in the trials, of whom 1466 received transplantation of stem cells (1241 with BM-MNCs and 225 with MSCs) and 1023 participants were included in the control group which had received either placebo injection or standard therapy for AMI. The primary intervention for all participants was percutaneous coronary intervention (PCI) Stem cell transplantation (BM-MNCs or MSCs) was performed for the intervention group and the control group received either an injection of placebo or standard care based on the current guidelines. The route of stem cell delivery was intracoronary injection for the majority of trials, except one with intramyocardial , one witFor assessing the risk of bias in eligible studies, we investigated selection, performance, detection, attrition, and reporting bias. We evaluated if the studies had a clear method for random sequence generation stated in the manuscript or its protocol. Twenty-four studies presented an adequate method for random sequence generation –41, 47. For this meta-analysis, the primary goal was to compare two types of stem cells (BM-MNCs and MSCs) used for patients following acute myocardial infarction regarding their effect on left ventricular echocardiographic indices  and rehospitalization for heart failure. For providing an easier way for interpretation of subgroup difference between the two types of cells, we employed ICEMAN tool for our analyses. The summary of ICEMAN instrument made for this review is shown in Table p < 0.001, I2 = 57.3%) and MSC trials    were included for analysis of change in LVEF from baseline to 4–6 months of follow-up. A significant improvement in LVEF was seen in both BM-MNC trials , but no difference in the level of LVEDV was observed after transplantation of MSCs  . Eight BM-MNC trials and only one MSC trial were available for sensitivity analysis, and there was no significant change in LVEDV in BM-MNC trials , but a significant decrease in LVEDV was observed in MSC trial  .Twenty-three BM-MNC trials and six MSC trials reported changes in LVEDV during 4–6 months after stem cell therapy. There was evidence of a significant change in LVEDV following BM-MNC therapy , whereas in MSC trials there was no significant change in the level of LVESV   .For LVESV, twenty-three trials for BM-MNCs and six trials for MSCs were assessed. BM-MNC therapy resulted in a significant decrease in LVESV  .The rate of hospitalization for decompensated heart failure at the longest duration of follow-up was reported in fourteen BM-MNC trials and five MSC trials. For both groups, the rate of hospitalization did not differ significantly compared to the controls ; if this therapy was performed within the first 10 days after AMI, its effect might increase (5.65% vs. 3.07%). To the best of our knowledge, this meta-analysis is the first study conducted to compare the effect of two types of cell therapy in the patients with AMI.Effects of stem cell therapy after acute myocardial infarction have been widely studied. Bone marrow-derived mononuclear cells (BM-MNCs) and mesenchymal stem cells (MSCs) are two of the most common and accessible types of stem cells used in clinical studies, both types of which have shown to improve the ventricular indices, specifically ejection fraction , 49. ResBased on the results of TAC-HFT randomized trial, it can be assumed that MSCs might be more effective than BM-MNCs in improving the function of the left ventricle after AMI as well. In the subgroup analysis, we observed a significant increase of 2.13% in LVEF following transplantation of BM-MNCs, whereas there was a significant improvement of 3.71% for LVEF in AMI patients transplanted with MSCs (MSCs improved LVEF by about 1.6% more than BM-MNCs). For better interpretation of subgroup analysis between the two types of cells, we employed the ICEMAN questionnaire  in our rSince ventricular dysfunction and the subsequent decompensated heart failure carry the most cardiac-related precipitating factor for mortality of AMI patients , preventThis study also had several limitations. We included a non-randomized clinical trial for MSCs since trials of MSCs included a total of 451 patients, which were limited compared to BM-MNCs that had a total of 2038 patients. Different modalities were used for measuring ventricular indices such as echocardiography, CMR, SPECT, and LV angiography, and this can cause some differences in interpretations. Another issue was that the baseline ejection fractions for patients were different and ranged from 33 to 62, and this can significantly change the results of trials.This meta-analysis provided evidence that both BM-MNCs and MSCs enhanced ventricular function by improving LVEF and MSCs appeared to be superior to BM-MNCs regarding the improvement of ejection fraction although these results cannot be interpreted without a level of uncertainty. Other ventricular parameters including LVEDV and LVESV and the rate of hospitalization for heart failure had equivocal results.Additional file 1. Summary of the risk of bias in the included studies.Additional file 2. Forest plot of the effect sizes of changes in LVEF from baseline during the short-term follow-up (4-6 months) measured by echocardiography in acute MI patients who received an intracoronary injection of either BM-MNCs or MSCs before 11 days after diagnosis of acute MI compared to the control group who received standard therapy with or without placebo injection.Additional file 3. Forest plot of LVEDV changes measured by echocardiography in acute MI patients receiving either standard therapy (with or without placebo injection) or autologous intracoronary injection of stem cells before 11 days of diagnosis based on the type of cell (BM-MNCs or MSCs).Additional file 4. Forest plot of comparison of changes in LVESV over the follow-up period measured by echocardiography in patients with acute MI who received intracoronary injection of stem cells based on the type of cells (BM-MNCs or MSCs) before 11 days after diagnosis of MI compared to the control group.


With the rapid emergence of extended Field-of-View PET-cameras several new applications for radiopharmaceuticals become within reach. Main reason is the significant increase of the sensitivity of the PET-camera so that much less radioactivity can be administered. Issues that that hampered development or use of PET-radiopharmaceuticals become realistic again. Molar activity requirements can become less strict. New low-yielding radiochemistry methods may become applicable. Carbon-11 labelled compounds can revive and potentially be shipped to nearby PET-facilities. PET-radiopharmaceuticals with slow kinetics in comparison to their half life can still be used. As additional infrastructure and equipment will likely remain unchanged and keep the same sensitivity therefore there will be issues with kinetic modelling requiring analysis of plasma or metabolites samples with lower count rate. Besides the potential revival of failed radiopharmaceuticals, novel challenges are ahead to develop novel radiochemistry based on thus far unsuitable (low yielding or time consuming) reactions. With the rapid emergence of long axial field of view positron emission tomographs (PET) a wide range of new opportunities has become available in the field of nuclear medicine –4. A colImproved image quality and high signal to noiseImaging with lower injected dosesImaging kinetics with greater temporal rangeImaging longer axial FOV (LAFOV)The extension of the axial field of view of the PET scanners provides a combination of the following advantages:In this paper it is described how each of these advantages may recreate interest in previously failed PET radiotracers.89Zr monoclonal antibodies FDG with FAP or PSMA binding PET-tracers or with radionuclides used for radionuclide therapy in a way of measuring the efficacy of treatment at voxel level CO2 and [11C]CH4 produced by the cyclotron. These non-radioactive carriers need to be excluded from the synthesis system as these will be converted to the non-radioactive radioligand in the same batch [In practice the less strict requirement to obtain high me batch .18F]enzalutumide. Though preclinical results were very promising, activity yields were that low that human studies were not possible. Examples of low-yielding reactions are multicomponent reactions and Diels-Alder reactions. Currently such methods have been abandoned or are solely used by a few highly trained research groups. This case may be especially true for 11C. It may also become possible to translate cold organic chemistry reactions that need longer reaction times into PET-radiolabelling procedures. One could also compromise on the use of less (expensive) precursor for radiolabelling allowing lower radiochemical yields being still enough for extended FOV PET-cameras.Several low-yielding production methods, including multi-step radiolabelling procedures that required long reaction times as compared to the half-life of the radionuclide such as multi-component reactions  or gave 18F-radiotracers are gradually taking over the 11C-analogs because the longer half-life of 110 min makes 18F-radiotracers more convenient from logistics point of view gallium chloride, or aluminium [18F]fluoride. These labelling procedures can be performed under mild conditions that do not compromise the integrity of the peptide/protein. Moreover, these short-lived isotopes are broadly available, can be used in many centres worldwide and have already been used successfully to label peptides and small proteins. Also, when accurate quantitative analysis of PET data by pharmacokinetic modelling of the binding kinetics of a tracer is required, the extended FOV PET camera can be of additional value deprenyl FDG FDG . Further18F]FDG .The extended FOV PET cameras that are currently available are much more expensive than regular PET-CT cameras. These costs might be compensated for if the camera can be used as a high throughput system for regular patient care. Usually, business cases for the acquisition of an extended FOV PET camera are based on the fact that more patients can be scanned, because of the shorter acquisition times . UsuallyWith the emerging opportunities and especially the increased sensitivity accompanying the extended FOV PET-cameras, there are several new possibilities for PET-tracers development both in the radiochemistry development as in the imaging and clinical application of these radiopharmaceuticals. Besides the potential revival of failed radiopharmaceuticals, novel challenges are ahead to develop novel radiochemistry based on thus far unsuitable (low yielding or time consuming) reactions.To fully benefit from the reported advantages also innovation is required for the supporting technology, equipment and infrastructure.


One million older Americans retire annually. While these transitions are not generally associated with poor mental health, the broader macro-economic context in which retirement transitions take place may shape how they relate to mental health. The objective of this study was to use state-of-the-art natural language processing (NLP) to develop a model to identify retirement transitions from textual data in the National Violent Death Reporting System (NVDRS), and to use that model to examine how the number of suicides related to retirement transitions changed during the recovery from the Great Recession. Data come from the NVDRS , a state-based registry of suicide deaths. We used RoBERTa to train a NLP model to identify retirement transitions  from 1,291 annotated sentences from NVDRS text narratives of suicide decedents aged ≥55 (model performance: F1=0.92). Applying this model, 19.35 of every 1,000 suicides among decedents aged ≥55 years mentioned a retirement transition. Decedent characteristics associated with retirement transitions were younger age (< 75 years), having a college education and experiencing financial problems. The probability that a narrative referenced a retirement transition increased 1.495-fold during the Great Recession (2007 - 2009) and declined during recovery (2009-2016) before beginning to increase again. Findings illustrate the utility of NLP methods to identify workforce transitions from NVDRS narratives, and further understanding the impact of macro contextual events like the Great Recession on population mental health.


Injury to the ocular lens perturbs cell-cell and cell-capsule/basement membrane interactions leading to a myriad of interconnected signaling events. These events include cell-adhesion and growth factor-mediated signaling pathways that can ultimately result in the induction and progression of epithelial-mesenchymal transition (EMT) of lens epithelial cells and fibrosis. Since the lens is avascular, consisting of a single layer of epithelial cells on its anterior surface and encased in a matrix rich capsule, it is one of the most simple and desired systems to investigate injury-induced signaling pathways that contribute to EMT and fibrosis. In this review, we will discuss the role of key cell-adhesion and mechanotransduction related signaling pathways that regulate EMT and fibrosis in the lens. The vertebrate ocular lens is a highly specialized transparent tissue of ectodermal origin that separates the anterior of the eye from the posterior. The lens is encased in its own basement membrane and is mainly composed of epithelial cells, which occupy the anterior part of the lens, and the fiber cell mass that makes up the remaining lens volume. Any perturbation in the structural organization or function of these cells results in opacification of the otherwise transparent ocular lens, causing a cataract. Cataract continues to be the second largest cause of visual impairment leading to blindness across the world, affecting nearly 94 million people with an overall financial burden of US $6.9 billion . Currentvia Smad-dependent pathways (TGFβ is a cytokine that has been shown to be a key modulator of the fibrotic cataracts PCO and anterior subcapsular cataract (ASC). Indeed, the aqueous humor from patients having undergone cataract surgery exhibits increased levels of active TGFβ , and TGFpathways . Howeverpathways .Although active TGFβ has been shown to be a major inducer of lens EMT and fibrosis, lens injury studies suggest that earlier, upstream events are required for activation of TGFβ and its sustained expression . The seca and β subunit, including 18 a and eight β subunits identified in mammals that can partner to form 24 different integrin receptors that bind specific ligand or set of ligands . Studies that have directly targeted αV integrin through conditional knockout in the murine lens have demonstrated its role in EMT and lens fibrosis . For exaRecent studies have also demonstrated that changes in the lens capsule, the matrix of the lens, can also contribute to EMT. For example, studies have shown that advanced glycation end products (AGEs) present in the lens capsule can potentiate TGFβ2-mediated EMT in human LECs and this occurs through the upregulation of both the canonical and noncanonical pathways . Interesin vitro and in vivo model systems  -actin assembles to form filamentous (F) –actin. During this process, actin binding proteins (ABPs) including myocardin-related transcription factors (MRTFs) dissociate from G-actin complex and translocate to the nucleus. Within this compartment, MRTF forms a complex with serum response factor (SRF) to regulate the expression key EMT genes . Therefof MRTF-A . A follof MRTF-A . These af MRTF-A . These oactility .et al performed a series of immunohistochemistry (IHC) analysis on lenses from mice upon needle injury. The lens epithelium of these mice showed increased expression of TGFβ1, fibronectin and a-SMA. As expected, the epithelium of injured lenses also showed increased activation of MLC9, and thus Rho signaling, suggesting an important role of Rho kinase signaling in the induction of EMT in lens upon injury . Taken together, these studies show that Rho/ROCK signaling is central to EMT induction in the lens either upon injury or induced by growth factor, and therefore modulating the expression and/or activation of RhoA/ROCK signaling might serve as a possible prognosis for EMT-mediated fibrosis in the lens and PCO.One of the important outcomes of Rho kinase signaling is actin cytoskeletal remodeling, which mainly occurs through polymerization of G-actin into F–actin fibers. F-actin, along with actomyosin, forms stress fibers that upon its interaction with focal adhesion points and cell junctions play an important role in cell motility, shape, and morphogenesis . Epithel-catenin . The forring EMT . Stabili in LECs  , mainly integrins, to the F-actin in the actin cytoskeleton and fibronectin expressed in the ECM by myofibroblasts . The foclocation . Recent via Rho/ROCK pathway. Inhibition of Rho/ROCK pathway also prevented cell elongation along with a decrease in Piezo1 density at the cell extension points (One of the major causes of EMT-mediated age-related fibrotic cataract is modulation of interaction of LECs with its basement membrane, the lens capsule, resulting from the changes in the matrix architecture of the lens capsule due to aging . Such chn points . These sInjury-induced repair results from collective migration of epithelial cells to the wounded area, a process that is controlled by partially transformed mesenchymal-like leader cells . These mUsing a mock cataract surgery model in chick, Walker et al observed increased expression of vimentin intermediate filaments in the lamellipodia of the mesenchymal-like leader or repair cell population located in the lens equatorial region . These cRepair cells following mock cataract surgery show increased presence of soluble vimentin, specifically in the wound activated mesenchymal cells that localize to the leading edge of the wound. The soluble vimentin is released extracellularly in response to injury where it is known to mediate the differentiation of leader cells to myofibroblasts . The preAnother mechanism through which extracellular vimentin might be contributing to the increased cell migration and invasion is FAK signaling. In the mock cataract injury model, vimentin colocalized with prominent paxillin-rich adhesion plaques at the tips of the lamellipodia of migratory leader LECs . The colIn recent years, there has been increased focus on understanding how injury contributes to EMT-mediated fibrosis in the lens. These studies point towards cell adhesion molecules as key players, responsible for the induction and progression of EMT in the lens, either independently or through activation of TGFβ signaling. For example, adhesion molecules such as the integrins have been shown to play an upstream role in lens induced-EMT and do so, at least in part, through activation of the conventional TGFβ signaling pathways following injury. Interaction of lens matrix AGEs with RAGE is also known to play a critical role during TGFβ-induced EMT in the lens. Furthermore, injury to the lens modulates mechanotransduction-mediated signaling including activation of YAP and Piezo1, both of which require Rho/ROCK-induced FAK signaling. FAK-mediated Rho/ROCK signaling may play an important role in enhanced cell migration, mediated by increased expression of extracellular vimentin during wound healing in the lens. As outlined in this review, many of the cell-adhesion mediated signaling pathways coordinate with one another to induce EMT and fibrosis in the lens. However, further studies are needed to understand how these complex signaling pathways crosstalk with one another during both early events of lens injury as well as in the later progression of EMT and fibrosis.