The heterogeneous presentation of inattentive and hyperactive-impulsive core symptoms in attention deficit hyperactivity disorder (ADHD) warrants further investigation into brain network connectivity as a basis for subtype divisions in this prevalent disorder. With diffusion and resting-state functional magnetic resonance imaging data from the Healthy Brain Network database, we analyzed both structural and functional network efficiency and structure-functional network (SC-FC) coupling at the default mode (DMN), executive control (ECN), and salience (SAN) intrinsic networks in 201 children diagnosed with the inattentive subtype (ADHD-I), the combined subtype (ADHD-C), and typically developing children (TDC) to characterize ADHD symptoms relative to TDC and to test differences between ADHD subtypes. Relative to TDC, children with ADHD had lower structural connectivity and network efficiency in the DMN, without significant group differences in functional networks. Children with ADHD-C had higher SC-FC coupling, a finding consistent with diminished cognitive flexibility, for all subnetworks compared to TDC. The ADHD-C group also demonstrated increased SC-FC coupling in the DMN compared to the ADHD-I group. The correlation between SC-FC coupling and hyperactivity scores was negative in the ADHD-I, but not in the ADHD-C group. The current study suggests that ADHD-C and ADHD-I may differ with respect to their underlying neuronal connectivity and that the added dimensionality of hyperactivity may not explain this distinction. Attention deficit hyperactivity disorder (ADHD) remains one of the most prevalent neurobehavioral disorders of childhood and adolescence, affecting social, emotional, and academic functioning. The DSM-V  segregatNeuroimaging findings in ADHD using diffusion tensor imaging (DTI) or resting-state functional MRI (rsfMRI) support the concept that a dysfunction in neurocircuitry may underlie this disorder and that differences in neural connectivity could distinguish between subtypes see –16. BaseAlthough a number of studies have examined structural circuitry with DTI –39 and fAccording to the brain network theory, the structural network (white matter tracts) constrains the functional brain network , but functional connectivity also deviates from the observed structural architecture , 43. In The degree of coupling between the structural and functional networks (SC-FC) differs according to the brain state or pathology. SC-FC coupling can help characterize brain disorders such as schizophrenia , epilepsIn this study, we explored the SC-FC coupling in the DMN, ECN, and SAN, intrinsic networks in the brain, using a database  from the Healthy Brain Network (HBN) database . We prim−7). No significant differences in Wechsler Intelligence Scale for Children [WISC, We used subject data from the Healthy Brain Network (HBN) database  for thisen WISC,  was founWe analyzed 201 subjects’ diffusion MRI, resting-state fMRI, and T1-weighted MRI data selected from the available releases (1 and 2) of the HBN database  accordinb-values . Following the procedure for multiple b-value diffusion imaging data analysis [https://www.fmrib.ox.ac.uk/fsl) in the individual’s diffusion MRI space [We constructed a structural connectivity network (SC) for each participant with 90 network nodes from cortical and subcortical regions defined according to the automated labeling (AAL) map . The difanalysis , we usedRI space . First, RI space . We thenTo create the structural networks, we performed “BedpostX” (Bayesian estimation of diffusion parameters obtained using sampling techniques) that implements Markov Chain Monte Carlo sampling to test propagation directions according to probabilistic orientation distribution at each voxel . To estihttp://www.fil.ion.ucl.ac.uk/spm, Wellcome Trust Centre for Neuroimaging, London, UK) [http://neuroimage.yonsei.ac.kr/mnet/), which offers graph analytical functions for fMRI and DTI. All fMRI data underwent slice scan time correction, head motion correction, co-registration of T1-weighted images to the first EPI, and spatial normalization for converting the functional EPI into MNI template space using nonlinear transformation. The fMRI time-series for each of the 90 AAL regions used in the structural analysis was obtained from the normalized fMRI data by applying principal component analysis to all the voxel time series from each region to extract its representative temporal activity . We then regressed out six rigid motion parameters and their derivatives, three principal components from the white matter and the cerebrospinal fluid masks, linear and quadratic regressors. A high-pass filter with a cutoff frequency of 0.009Hz was applied. Functional connectivity matrices were constructed by calculating Fisher’s z-transformation of the correlation coefficients between every pair of the 90 brain regions.To construct a functional connectivity network (FC), we conducted standard preprocessing of the fMRI data using SPM12   and an iTo investigate the topological characteristics of ADHD-related brain subnetworks, we evaluated the structural and functional features of the DMN, ECN, and SAN. According to previous studies –70, we cG with the total number of nodes N, global efficiency Eglob is defined as the average of all node efficiencies:d is the length of the shortest path between nodes i and j.As the structure-function coupling does not provide detailed information on whether the functional network deviates from the structural network in a positive (compensatory) or negative (as a result of pathology) mode relative to the symptom, we used global efficiency as an interpretive clue in terms of information transfer efficiency . For eacTo evaluate global efficiency, we constructed the network by thresholding the connectivity matrices: structural networks were constructed with one or more fiber counts while functional networks were thresholded with a positive value corresponding to a FDR  < 0.05.For the metric of SC-FC coupling, we followed , 73 and https://github.com/Jfortin1/ComBatHarmonization).To reduce effects derived from the two different data acquisition sites, we harmonized the network property and SC-FC couplings using a ComBat model –78 that To evaluate group differences in the multi-site harmonized structural and functional connectivity features and the SC-FC coupling of the global network, we employed a one-way analysis of covariance (ANCOVA), with age and sex as covariates. For the functional connectivity analysis, we used FDR < 0.05 as the criteria for statistical significance.In order to add a behavioral dimension, we conducted correlation analyses of the individual subject scores on both the Strength and Weaknesses of ADHD-symptoms and Normal-behavior (SWAN) battery with SC-FC coupling. First, we conducted a correlation analysis between hyperactivity and inattention scores to test whether a relationship between these scores manifests in either of the two subtypes. These two scores differentiate the two subtypes and construct two different domains. Second, we conducted a correlation analysis between the hyperactivity scores and SC-FC couplings and between the inattention scores and SC-FC couplings in the DMN to assess subtype differences.The network analysis results of the whole brain network are presented in The analysis of covariance (ANCOVA) with age and sex as covariates revealed significant group differences in global efficiency of the structural connectivity within the DMN  = 7.28, p = 0.0009), ECN  = 5.24, p = 0.0061), and SAN  = 6.70, p = 0.0015). As shown in −8)  and ADHD-C  . A statiThe SC-FC coupling in the DMN of ADHD-I demonstrated a significant negative correlation with the hyperactivity score  ; whereasIn the brain subnetworks relevant to ADHD, an analysis of both structural efficiency and SC-FC coupling reveals differences between ADHD-I, ADHD-C, and TDC.The structural properties differ more than the functional properties of networks between children with ADHD and TDC. Only structural connectivity see  and the We found lower global structural efficiency in the whole-brain network of children with ADHD  comparedTo explore characteristics specific to ADHD subtypes, we focused on ADHD-related subnetworks, the DMN, ECN, and SAN, which other groups have used to identify impairments in various brain diseases , 55, 73.Similar to our whole-brain analysis, we found reduced global efficiency in the structural component of the DMN, ECN, and SAN in children with ADHD (more reduced in the ADHD-C group) relative to that in the TDC group . Again, The fundamental question of how flexible functions emerge from the structural network has prompted interest in the relationship between structural and functional connectivity , 43. TheIn these studies, high SC-FC coupling  has often been interpreted as a marker of rigidity or inflexibility at the cognitive or behavioral level. However, the biological mechanism of SC-FC coupling is not fully understood. Multifactorial explanations for a higher order relationship between structure and function include such possibilities as polysynaptic connections, anti-correlations via connections to an inhibitory input, and differences in neuromodulation . Jang, KThe strong coupling in the DMN in children with ADHD-C compared to children with ADHD-I suggests that the DMN in the ADHD-C group may operate with fewer indirect polysynaptic connections. Whereas, at the symptomatic level, the negative correlation between hyperactivity and SC-FC coupling indicates that this symptom domain may contribute to cognitive control in the ADHD-I group. This aspect of executive functioning includes both the ability to stop one type of behavior and the capacity to engage with a different interest or initiate an alternative behavior. Incorporating measures of both cognitive flexibility and cognitive control into future studies of ADHD subtypes and SC-FC coupling could help evaluate the significance of this finding. The SC-FC coupling measure (correlation coefficient) indicates how much the functional network converges to the “baseline” structural network. Thus, the rigidity or inflexibility (the degree of convergence) should be interpreted concerning the “inefficient” structural network in ADHD, particularly in the ADHD-C subtype.In the ADHD-C subtype, the interactions between brain regions in the DMN appear to be strongly constrained by an inefficient structural network topology. Considering that the DMN is involved in self-reflection, mind wandering, and internally oriented processes –16, 84, Currently, the DSM-V  segregatAlthough we have primarily explained the DMN of children with ADHD-C in terms of functional inflexibility over an inefficient structural topology, the ECN and SAN exhibit comparable degrees of structural network inefficiency. The ADHD-C group displayed higher SC-FC coupling in the ECN compared to controls, but no significant difference in SC-FC coupling between ADHD subtypes emerged. Of note, the SC-FC couplings in the SAN and ECN are relatively weak compared to the coupling observed in the DMN. A portion of the children measure in the zero-coupling zone (zero correlation coefficients). In addition, some children display anti-correlated SC-FC coupling in the SAN and ECN. A negative functional connectivity transmitted over a structural edge may explain the anti-correlated coupling between the SC and FC subnetworks of these children. Thus, the ECN and SAN may not submit to the same explanation as the DMN.We cannot generalize that the relationship between hyperactivity symptoms and the SC-FC coupling in the DMN extends to the other subnetworks. In addition, the inattentive symptoms in both ADHD-I and ADHD-C may not be attributable to dysfunction in a specific subnetwork but may relate to a combination of different subnetworks, for example, the ECN, SAN, and DMN, or to abnormal interactions between networks. These subnetworks may function differently in TDC, in children with ADHD-I, and in children with ADHD-C. This interpretation is consistent with the constellation of multiple dysfunctions witnessed in the DMN , 85, ECNThis study has several limitations. First, our control group of TDC does not reflect the gender imbalance found in the ADHD samples. A recent metanalysis of human connectome studies did not find significant gender differences , but thiSecond, the Healthy Brain Network (HBN) database incompletely documents the history of stimulant use and current medication status of the individual participants—Only 51 children over age 10 evaluated in the current study had a complete drug screening before the MRI scans. Prolonged stimulant use can enhance gray matter volume  and may Third, when the current study was conducted, the MRI and behavioral data of the release 1 and 2 were fully accessible. Thus, we consider the current results preliminary at this point and leave the analysis with more detailed parcellation maps and more data for a further study.Fourth, graph analysis of the brain requires the nodes, or anatomical parcellations to cover the entire cortex. We have followed this stipulation, but in doing so, we may have obscured more fine-grained details about the connectivity between brain regions. In particular, the extraction of time courses from relatively large brain regions that may support varied functions could effectively have washed out group differences in functional connectivity. Conversely, we cannot rule out that the heterogeneous composition of a node used in this study may increase the detection power between groups considering context or state-dependent changes in the functional atlas even within an individual . Since tFifth, the computations used to establish the functional connectivity of networks in this study do not incorporate deactivations. Because cognitive tasks and attention may rely on the DMN’s ability to effectively deactivate with respect to other networks, such as the ECN and the SAN, this analysis may overlook a crucial mechanism for the DMN’s role in ADHD. Further studies on the coupling between networks may be able to address this issue more successfully. Finally, the reliability of the functional connectivity of rsfMRI has been an issue . Thus, wIn summary, we investigated attention-related brain subnetworks in children with ADHD-I and ADHD-C using the relationship between structural and functional networks. We found SC-FC coupling differences between children with ADHD and TDC and between ADHD subtypes in the ADHD-related subnetworks . Although SC-FC coupling in the DMN significantly differed between ADHD subtypes, the subnetworks seem to work together to manifest a different degree of inattentiveness and hyperactivity in the ADHD-I and ADHD-C groups. Given that structural differences between individuals with ADHD and controls has been demonstrated in children but not adults, further work on the SC-FC coupling should include longitudinal data . These fS1 Table(DOCX)Click here for additional data file.S1 Data(ZIP)Click here for additional data file.


Few studies examined socio-ecological factors and leisure time physical activities (LTPA) and rarely focused on self-regulation and social capital, which might play a significant role in impacting people’s physical activity behavior. This study aimed to examine the direct and indirect effects of individual level , interpersonal level (self-regulation), social level , and environmental level factors  on LTPA among older adults.A cross-sectional study was conducted in 737 older adults from Sichuan, China. Structural equation modeling (SEM) analysis was used to examine the associations of individual, interpersonal, social, and environmental level factors with LTPA.The mean age of all participants was 71.22 , and 56.1% of them were women. The SEM results showed that individual level variables , self-regulation  and social capital  could all directly affect LTPA while there was no significant association of perceived physical environment with LTPA. Self-regulation served as a bridge linking social capital and LTPA. Individual level variables contributed the largest total effect (0.32) on LTPA. Self-regulation and social capital had the same total effect (0.18) on LTPA.Factors on three levels were all significantly associated with LTPA. Interventions that incorporate individual, interpersonal, social factors may be considered to promote LTPA in older adults. Self-regulation should receive more attention in future interventions.The online version contains supplementary material available at 10.1186/s12877-021-02730-9. Severe population aging is projected to occur in most parts of the world in the next several decades . In ChinThe socio-ecological model suggests that behaviors are influenced by an interaction of individual, interpersonal, social, and environmental level factors . A few sFurthermore, despite that correlates of physical activity have been widely examined using the socio-ecological model, little is known about the socio-ecological factors of leisure time physical activity (LTPA), the most important domain of physical activity , especia2, villiage:853, population:1,171,200). Third, four villages  were randomly selected in the rural areas of the city. Random selections were generated by a computer program (www.random.org). Fourth, a total of 737 participants (aged from 60 to 97 years) were randomly recruited from the four villages. Twenty-four of them were excluded due to immobile/deaf, severe mental disease, or incomplete identifying information. All of the eligible participants were invited to a face-to-face survey, which usually took 20–30 min. Informed consent was obtained from each participant before conducting the survey. The study protocol was approved by the Sichuan University Medical Ethical Review Board (K2019073).Data used in the study comes from a cross-sectional design, population-based survey conducted in October 2020. A multi-stage random sampling method was used to recruit a sample aged 60 years and older in Sichuan Province, western China. First, Chengdu was randomly selected from 18 cities of Sichuan Province. Second, Jianyang was randomly selected among 20 regions in Chengdu. Jianyang is located in the western part of the Sichuan Basin  . The scoThe survey included questions on sociodemographic factors including age, sex, marital status, education, employment status, and annual household income (RMB).Self-efficacy was assessed using a 9-item scale , rated fScales measuring perceived benefits (12 items) and barriers (6 items) were adapted from a previously validated scale, Exercise Benefits/Barriers Scale (EBBS) . The exaSelf-regulation was assessed with a scale adapted and validated for older adults . The scaThe instruments to assess social capital included the individual- and family- (IF-) based social capital scale and the community- and society- (CS-) based social capital scale . The scaPerceived physical environment consisted of seven separate items . Examples of the items were “You often see people out on walks in your neighborhood.” and “The streets are well lit.” The items used were adapted from a previous study . The intMean and standard deviation were calculated for continuous variables. Frequency and percentage were calculated for categorical variables. Structural equation modeling (SEM) analysis was used to explore the associations of individual level, interpersonal level, social level, and environmental level factors with LTPA. The structural equation model included the path from individual level  to LTPA; the path from self-regulation to LTPA; the path from social capital (latent variable) to LTPA; the path from perceived physical environment (latent variable) to LTPA; and the path from social capital (latent variable) to LTPA via self-regulation Fig. . The comTable The structural equation model for LTPA in Fig. Table The study aimed to explore the factors influencing LTPA in older adults based on the framework of the socio-ecological model. The SEM analysis showed that individual level variables , interpersonal level variable (self-regulation), and social level variable  were significantly associated with LTPA, while environmental level variable  was not significantly associated with LTPA in older adults. Self-regulation mediated the pathway from social capital to LTPA. These socio-ecological factors may play an essential role when designing programs to promote leisure time physical activity for older adults.Environmental factors were considered to be a key direction for future research on geriatric health . Most stExisting literature suggested that social capital interventions were effective in improving social support , and higSelf-regulation, as one of the most important factors to translate physical activity intention into action , was fouThe study indicated that individual level variables had the largest total effect on LTPA, with self-efficacy having the greatest impact on individual level. In other words, self-efficacy was one of the most influential factors affecting LTPA in our study, and it has been widely acknowledged by previous literature , 19, 42.Several limitations of the study are noteworthy. First, our data were based on self-report from older adults, recall bias may not be avoided. Second, the cross-sectional design does not allow us to infer causality, warranting studies with longitudinal designs to verify such findings. Third, physical activities other than LTPA  were not controlled for, which may overestimate the associations. Fourth, both intrapersonal and interpersonal dimensions are important in self-regulation , but thiDespite these limitations, our study was one of the first studies examining associations between socio-ecological factors and LTPA in older adults, and including self-regulation and social capital.We found that self-regulation mediated the pathway from social capital to physical activity. This finding may provide new ideas for the design of LTPA intervention programs for older adults. For example, considering the sharply reduced health effects of social capital in older adults over the age of 80 , interveWe also found that factors from three levels  were significantly associated with LTPA. A combination of individual level, interpersonal level, and social level factors should be considered in future physical activity interventions.In the study, we found that self-efficacy, perceived benefits and barriers, self-regulation, and social capital were significantly associated with LTPA while perceived physical environment was not significantly associated with LTPA in older adults. Self-regulation mediated the pathway from social capital to LTPA. These findings suggest that programs promoting LTPA in older populations based on socio-ecological model are most likely to be successful. The finding that self-regulation was not only a direct impact factor of LTPA but also a mediator between social capital and LTPA, may suggest that self-regulation should receive more attention in future interventions in this group. Longitudinal studies are needed to verify such findings.Additional file 1. Effects of individual level variables, self-regulation, social capital, and perceived physical environment on LTPA. There were no significant association of perceived physical environment with LTPA; *ρ < 0.05, ***ρ < 0.001.Additional file 2. Effects of individual level variables, self-regulation and social capital on LTPA in older adults. The path from individual level to self-regulation was added in the model. *ρ < 0.05, ***ρ < 0.001.


Asparaginase plays an integral role in chemotherapy for acute lymphoblastic leukemia (ALL). We present a 69-year old woman with refractory ALL, who developed asparaginase-induced hepatotoxicity and cholangiopathy after starting intravenous PEG-L-asparaginase-based chemotherapy. The patient was ultimately treated with the combination of L-carnitine and vitamin B complex, resulting in normalization of liver enzymes levels. This case highlights the consideration of PEG-L asparaginase chemotherapy-induced liver steatosis, injury, and cholangiopathy as well as the role of L-carnitine and vitamin B complex as treatment. Drug-induced liver injury is a complex and diverse syndrome that has been attributed to a variety of therapeutic and non-therapeutic agents . The toxA 69-year-old female was seen in hospital consultation for abdominal pain and altered mental status, after being admitted five days prior for a planned chemotherapy treatment.She has a medical history of T-cell ALL, diagnosed six months prior to presentation. This diagnosis was made based on biopsies of her submandibular lymph nodes and subsequently, her bone marrow. She had undergone induction chemotherapy with the PETHEMA protocol  two months after diagnosis, followed by Hyper-CVAD therapy  for persistent disease after induction. A month prior to her hospitalization, a repeat bone marrow biopsy demonstrated low-level but persistent lymphoblastic leukemia. Additional chemotherapies were attempted, but she was unable to tolerate treatment with Vincristine and Nelarabine secondary to adverse side effects, which ultimately lead to the scheduled hospitalization for augmented hyper-CVAD therapy with PEG-asparaginase. At the time of evaluation, she reported mild nausea but denied vomiting, diarrhea, fever or chills. With ambient air her oxygen saturation was 98%, she was afebrile, but demonstrated tachycardia and tachypnea. Physical examination also elucidated scleral icterus as well as right upper quadrant and epigastric tenderness. Laboratory tests revealed an aspartate aminotransaminase (AST) of 45 U/L, alanine aminotransaminase (ALT) of 72 U/L, alkaline phosphatase (Alk phos) of 282 U/L and total bilirubin (TB) was 2.0 mg/dL. Lipase was elevated at 1687 U/L; greater than three times the upper limit of normal at our laboratory. She was diagnosed with probable drug-induced pancreatitis and drug-induced cholestatic liver injury. An extensive investigation was carried out to determine any other causes of liver injury and pancreatitis. Serological testing revealed that she was immune to Hepatitis B and Hepatitis A, and negative for Hepatitis C infection. An ultrasound of the abdomen revealed hepatic steatosis, absent gall bladder, and absence of ascites  was obtained, which showed interstitial edematous pancreatitis, bilateral pleural effusions, but absent intrahepatic or extrahepatic biliary dilatation or changes concerning for cholangitis Figure .There was a suspicion of PEG-Asparaginase as the cause of her symptoms and multi-organ injury given the presence of concomitant hepatitis and pancreatitis. Her symptoms of nausea, abdominal pain, and altered mental status improved with a low-fat diet, intravenous fluid resuscitation, and analgesia. She was concomitantly started on L-carnitine supplementation and Vitamin B complex for presumed Asparaginase-induced liver injury. As her liver enzymes and bilirubin continued to increase despite these interventions, a liver biopsy was performed. The pathology revealed severe hepatic steatosis and moderate cholestasis Figure , and milThere was no evidence of leukemia, nodular regenerative hyperplasia, granulomas or significant fibrosis. Her liver enzymes, alkaline phosphatase, and bilirubin started to show improvement on day 10 of IV L-carnitine and continued toward normalization thereafter Figure .Since discharge, the patient has had a bone marrow biopsy without ALL on morphology but 0.06% abnormal lymphoblasts on flow. In order to maintain remission while working on performance status, the patient was started on maintenance chemotherapy with POMP  and she continues to tolerate her current therapy. She is planning to be a part of a clinical trial with CAR-T (chimeric antigen receptor T cell) immunotherapy, once her performance status improves.Since its introduction to the field of pediatric oncology in the 1960s, Asparaginase has been an integral part of chemotherapy regimens for treating ALL , 3. It iThere is a myriad of adverse effects associated with asparaginase, which include varying severities of hypertriglyceridemia, acute pancreatitis, venous thrombosis, hypersensitivity reactions, neurologic dysfunctions as well as hepatotoxicity and bile duct injury -7.Hepatotoxicity due to asparaginase use may present itself as a self-limiting mild elevation of liver enzymes and bilirubin and in rare cases, severe liver injury with associated death ,9. AlthoSpontaneous resolution of hepatitis will occur in most cases of asparaginase-induced liver injury, and treatment is largely supportive. However, the use of L-carnitine has been studied in the treatment of liver toxicity due to asparaginase, carbon tetrachloride, valproic acid, and arsenic -14. The Additionally, our patient had a continued rise in her liver enzymes and bilirubin even after a few days of treatment. This delayed improvement in liver injury has been documented in the literature as well .We believe that our patient sustained liver injury due to PEG-Asparaginase use, and this improved overtime after administration of L-carnitine and vitamin B complex. It is important to note, however, that the beneficial effects of the combination of L-carnitine and vitamin B complex infusions have not been studied in a randomized controlled trial and that this may be a normal course of L-asparaginase induced hepatotoxicity, and therefore the resolution of liver injury cannot be fully ascribed to these medications and can only be inferred. It is nevertheless plausible to commence this combination treatment regimen in patients with severe asparaginase-induced liver injury.


In today’s competitive e-commerce markets, it is crucial to promote product satisfaction and to quickly identify purchase intention in decision-making consumers. The present investigation examined the relationship between perceived garment fit and purchase intention, together with how product presentation methods (mannequin versus self-model) contribute to decision-making processes of clothing. Thirty-nine female volunteers were scanned using fMRI while performing an online shopping task. In Part 1, univariate analysis was conducted between garment fit and product presentation factors to assess their effects on purchase deliberation. In Part 2, univariate, multivariate pattern, and psychophysiological interaction analyses were carried out to examine the predictive ability of fit evaluation and product presentation on purchase intention. First, garment fit × product presentation interaction effects on purchase deliberation were observed in the frontopolar cortex, superior frontal gyrus, anterior cingulate cortex, and posterior cingulate cortex. Part 2 demonstrated neural signals of the dorsomedial prefrontal cortex, premotor cortex, supplementary motor area, superior parietal lobule, supramarginal gyrus, superior temporal sulcus, fusiform gyrus, and insula to distinguish subsequent purchase intentions. Overall, the findings denote directed exploration, visual and action processing as key neural processes in decision-making that uniquely reflect garment fit and product presentation type during purchase deliberation. Additionally, with respect to the effects of purchase intention on product evaluation, the evidence conveys that mental interactions with products and social cognition are fundamental processes that capture subsequent purchase intention at the product evaluation stage. Consumers go through complex internal processes before making purchase decisions. As consumers are the backbone of all businesses, understanding the buying behavior is critical. Consumer purchase intention informs businesses about customers and purchase intention is one of the strongest indicators of future purchase decisions . MarketpWith the application of neuroscience to the understanding of consumer psychology , extensiWhen it comes to the fashion industry, there are numerous factors that influence the overall fit satisfaction of apparels, such as color, fabric texture, comfort, body type, function, personality, garment fit, and how products are presented to customers . In geneSeveral probable brain regions can be proposed for the neural basis of factors influencing consumer behaviors toward fashion products. For example, different methods of product presentation have not only indicated greater engagements of neural regions related to visual processing, mental imagery, and reward processing, but also have shown the effectiveness in altering purchasing behavior . Reward-Despite the intricate workings of the factors that influence the consumer process for fashion products, neural underpinnings of these factors have not yet been elucidated. This study aimed to understand the neural basis underlying garment fit, purchase intention, as well as mannequin and self-model product presentation methods through two parts. Part 1 investigated the neural effects of garment fit and presentation type on purchase deliberation. Here, we hypothesized that the items with garment fit presented on self-models would particularly engage the reward network including the ventral striatum and vmPFC during deliberation of purchase decision. Part 2 sought to identify brain regions that predict purchase intention under the hypothesis that the way decision makers interact with products during fit evaluation would uniquely capture the subjective intention-to-purchase and product presentation types, and this way would be reflected in neural areas associated with mental imagery, such as the SPL, SMG, and IFG, and social cognition, such as the dmPFC, TPJ, and STS.A total of 39 healthy female participants between the ages of 20 and 29 years were recruited via online advertisement . Exclusion criteria included left-handedness, pregnancy, and neurological or psychiatric diseases. All participants were provided informed written consent prior to partaking in the study, and the study was approved by the Institutional Review Board of Yonsei University Severance Hospital and carried out in accordance with the Declaration of Helsinki.During the fMRI scanning session, participants engaged in an apparel-purchasing task. Task stimuli were prepared before the scanning session. A set of 42 articles of top-only clothing was selected from various online shopping websites. To maximize generalizability, selected items consisted of short-sleeved shirts, long-sleeved shirts, and sweaters. Using Adobe Photoshop , all products were traced for manipulation and all brand labels (or any indication of such) were erased to eliminate the brand effects. Then, the manipulation-ready products were transposed onto a generic mannequin and a female model. The images of both the mannequin and female model were framed to show the bodies from the top of the head to above the knees and from shoulder to shoulder. Participants completed an online survey to approximate an appropriate market price for each item of clothing a few days prior to the fMRI scan and provided a picture of their own face. Self-model images of each participant were produced by superimposing participants’ faces onto the female model’s body to make each shopper feel like she was wearing the clothes .1The task sequence included two runs and 42 trials in each run of approximately 7 min 52 s. In the first run, 42 different articles of clothing were used in the form of 21 self-model and 21 mannequin images, with one per trial. The same 42 clothes were used interchangeably between self-model and mannequin images in the second run. Each trial consisted of two phases of 3 s, representing fit evaluation and purchase deliberation, to emulate the consumer decision-making process. In the fit evaluation phase, one of the prepared superimposed images of either the mannequin or the participant herself wearing an apparel was presented. At the bottom of the image appeared the question, ‘‘Will the clothes fit you well?’’ Together with this, a four-ticked Likert scale appeared with scores of 0: ‘‘not at all,’’ 1: ‘‘somewhat,’’ 2: ‘‘moderately,’’ 3: ‘‘very much.’’ Participants were instructed to indicate the level of garment fit by pressing a button, and the response was referred to as the fitness score. In the purchase deliberation phase, the identical image from the fit evaluation phase was displayed with the price along with the question, ‘‘How much do you want to buy?’’ Also displayed was the identical Likert scale. Participants’ responses were referred to as the intention-to-purchase score. In order to limit the influence of price information as the standards for the price of apparels vary from person to person, the prices were adjusted and presented in reference to the individual’s pre-reported price point. On average, the prices the participants saw were approximately discounted by 12%, where the highest markdown was by 50% and the highest markup was by 130% of the pre-reported price points. To encourage serious participation in the task, participants were informed that they could purchase one product of high intention-to-purchase at the end of the scanning session. The intervals were jittered with an average of 2.5 s (range: 1–4.5 s) between the phases and 3 s (range: 2–6 s) between the trials. The schedule of events and jitters were obtained using Optseq2.All functional scanning was performed on 3.0 Tesla MRI scanner  with a 32-channel head coil. For each participant, echo-planar imaging scans were acquired with the following parameters: repetition time = 2,000 ms, echo time = 30 ms, flip angle = 90°, number of acquisitions = 235, number of slices = 31, slice thickness = 3 mm with 1 mm interstitial gap, and matrix size = 80 × 80. A high-resolution T1-weighted structural scan was also obtained from each participant using a 3D gradient echo  after the functional scan.2). To allow for the stabilization of magnetization, the first five scans were discarded. The remaining images were corrected for slice-timing, realigned to correct for head-motion, and co-registered on the individual T1-weighted image. Then, the T1-image was spatially normalized to the MNI template and the resulting transformation matrices were applied to the co-registered functional images. The normalized images were smoothed with a Gaussian kernel of 6-mm full-width at half-maximum (FWHM).All images were preprocessed using Statistic Parametric Mapping 12  among the categories were examined using repeated-measures ANOVA. To determine garment fit, the participants’ responses during the fit evaluation phase were separated according to each participant’s fitness rating obtained during in-scan behavior; a score of 0 was deemed as having no garment fit (fit-absent) and scores of 1, 2, and 3 were deemed as having at least some garment fit (fit-present). The trials during the purchase deliberation phase were then labeled depending on the product presentation conditions (self-model and mannequin), thereby creating four categories (garment fit × product presentation). To assess the predictive ability of garment fit and product presentation on the subsequent purchase intention, differences in the fitness scores and RTs among the categories were assessed using repeated-measures ANOVA.Post hoc analysis was carried using paired t-test. All analysis of behavior data was computed using SPSS 25.0 .To determine purchase intention, participants’ responses during the purchase deliberation phase were categorized into intention-absent and intention-present for an intention-to-purchase score of 0 corresponding to having no intention to buy and scores of 1, 2, and 3 corresponding to having some purchase intention, respectively. The trials during the fit evaluation phase were then labeled depending on the product presentation conditions (self-model and mannequin), thereby creating four categories (purchase intention × product presentation). PUNC < 0.001. The multiple comparison problem was addressed using family-wise error correction at PFWE < 0.05 at the cluster level.Once preprocessed, imaging data was analyzed using a general linear model (GLM) at a single-subject level. The preprocessed images were separated into eight categories; the images obtained during the purchase deliberation phase were divided according to garment fit (fit-present and fit-absent) and product presentation (self-model and mannequin), and those obtained during the fit evaluation phase were divided according to purchase intention (intention-present and intention-absent) and product presentation (self-model and mannequin). Then, the BOLD signals for each category were modeled at the onset of each stimulus for the duration of RT (“variable epoch”) to factor out the effects of RTs , and theFor Part 2, as a complementary analysis to the mass univariate analysis, we performed multivariate pattern analysis (MVPA) for whole brain searchlight to demonstrate the brain correlates that are predictive of purchase intentions from the fit evaluation phase. The decoding toolbox optimized for SPM was used to decode brain regions showing unique neural patterns reflecting subsequent intention-to-purchase. As recommended by The regressors of the fit evaluation phase were labeled by the intention-to-purchase category, and data were split into half by the first and second run. Next, we took a cross-validated pattern correlation approach . A sphert-tests to examine the unique neural patterns predictive of subject’s subsequent intention-to-purchase. As MVPA has been known to increase sensitivity of cognitive states , but no main effect of product presentation or interaction effect of garment fit × product presentation. Post hoc analysis showed that the intention-to-purchase scores for fit-present items were significantly higher than the scores for fit-absent products . Analysis of RTs showed main effects of garment fit  and product presentation , but no interaction effect. Post hoc analyses indicated that RTs were significantly longer for fit-present than for fit-absent clothing  and showed shorter RTs toward self-models than toward mannequins .The summary of behavioral data is presented in Post hoc tests demonstrated that the bilateral dmPFC, right dorsolateral prefrontal cortex (dlPFC), right inferior temporal gyrus, bilateral midcingulate cortex, left hippocampus, and bilateral caudate showed greater activity for self-models than for mannequins, whereas the right SMG, bilateral precuneus, left STS, and bilateral fusiform gyrus exhibited greater activity for mannequins than for self-models.post hoc analysis are presented in t38 = 2.07, P = 0.046), lower for fit-present/mannequins than for fit-absent/mannequins , and lower for fit-absent/self-models than for fit-absent/mannequins . In the right SFG , whereas fit-absent items generated significantly lower activity for self-models than for mannequins . There was no significant difference in activation between fit-present and fit-absent within products displayed on mannequins , but the SFG activation was greater for fit-present than fit-absent items within self-models . In the bilateral ACC , whereas its activity was lower for fit-absent/self-models than fit-absent/mannequins . Fit-present items induced significantly lower activity than fit-absent items  within mannequins, but no significant difference was observed between fit-present and fit-absent items within self-models . In the bilateral PCC , whereas it was significantly lower for fit-absent/self-models than for fit-absent/mannequins . Within mannequins, the activity of fit-present condition was lower than that of fit-absent condition , but no difference was observed between fit-present than fit-absent products within self-models .The interaction effect of garment fit × product presentation was evident in the right frontopolar cortex (FPC), right SFG, bilateral anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex (PCC). Results from ight SFG , fit-preeral ACC , the acteral PCC , the actF1,38 = 491.84, P < 0.001) and product presentation , and a moderately significant interaction effect between the two factors . The fitness scores were significantly higher for garments that participants later identified as having intention-to-purchase than those without intention-to-purchase  and toward clothing displayed on a mannequin than on the participants themselves . Specifically, the fitness scores were higher for garments displayed on mannequins that were later identified as intending to purchase than for garments displayed on mannequins that participants did not intend to purchase . Also, the fitness scores were higher for intention-present clothing displayed on mannequins in comparison to intention-present clothing displayed on self-models . In contrast, the scores were higher for intention-present garments displayed on self-models than for intention-absent garments displayed on self-models . Regarding intention-absent products, the scores were higher when items were presented on mannequins than on self-models . The RTs showed a main effect of purchase intention , but displayed no main effect of product presentation and interaction effect. Post hoc analysis indicated that the RTs for intention-present apparels were significantly longer than for intention-absent clothing .The summary of behavioral data is also shown in Post hoc analyses showed that the right premotor cortex, left SPL, and right SMG were more activated for intention-present than for intention-absent clothing, whereas the bilateral dmPFC, right SMA, right SPL, left STS, left fusiform gyrus, left anterior insula, right posterior insula, and right dorsal striatum were more activated for intention-absent products than for intention-present products. Several clusters also showed the main effect of product presentation  and product presentation, and between purchase intention (absence/presence) and product presentation. Furthermore, because behavioral responses were obtained on a four-point Likert scale, it would be interesting to investigate the linear modulatory effect of behavioral data using parametric modulation in future studies.Conducting studies only in female participants and only in young adults may limit the generalizability of our interpretations, and participants’ general patterns of shopping behavior and favored styles of clothing were not accounted for. Although the price is a vital factor in shopping, this study did not allow direct examination of price effects; instead, only presented price information to control for its effects. Going forward, study designs should embrace price points to investigate how perceptions of price interact with consumer processes and product presentation types. In addition, to control for the price effect, it would have been more appropriate to include the difference between expected versus presented prices as a nuisance regressor rather than simply adjusting the prices based on each reference price. Although participants with clearly disproportionate behavioral responses between intention-to-purchase conditions were excluded, the analysis included some imbalance. Consequently, the classification accuracies of the brain regions containing intention-predictive information may have been biased by this imbalance. In similar light, the imbalance of data between fit-absent and fit-present was greater in Part 1 (effect of fit satisfaction). As such, the interpretation of the results should be read with caution.The present investigation surveyed the neural substrates of decision-making processes in online shopping for apparels. The findings of the study further the current understanding of the relationship between garment fit and purchase intention, and provide a comprehensive overview of neural correlates that characterize respective components. First, we established neural evidence for the notion that fit of clothing and modes of display have an impact on purchase decisions, suggesting that webstores should offer virtual displays of products to mitigate uncertainty and promote optimal decision strategies chosen during deliberation of purchase decision. Then the investigation discovered the neural basis of purchase intention. Reflected in the parietal lobules, prefrontal cortex, and sensorimotor-related regions, imaging data accentuated the employment of mental imageries. Collectively, the evidence featured directed exploration, visual and action processing as key factors that capture the essence of garment fit and product display during purchase deliberation, and mental interaction with products as a critical factor of fit satisfaction and purchase intention throughout the consumer process. Furthermore, the findings marked mental imagery and social cognition as predictive factors of purchase intention during fit evaluation.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by the Institutional Review Board of Yonsei University Severance Hospital. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.HK and J-JK conceived and designed the experiments. HK and JK performed the experiments. HK analyzed the data and drafted the manuscript. J-JK revised the manuscript. JK edited the manuscript. All authors contributed to the article and approved the submitted version.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.


Obesity increases the risk of pelvic floor disorders in individuals with obesity, including faecal incontinence. Faecal incontinence (FI) is a condition with important clinical and psychosocial consequences. Though it is associated with obesity, the effect of bariatric surgery on the prevalence and severity of FI is not well reported.To assess the effect of bariatric surgery on the prevalence and severity of FI in adult patients with obesity.This systematic review was conducted in accordance with the PRISMA statement. Two independent reviewers performed a literature search in MEDLINE, PubMed, Cochrane and Embase from 1 January 1980 to 12 January 2019. We included published English-language randomized control trials and observational studies assessing pre- and post-bariatric surgery prevalence or severity of FI. Random-effects models with DerSimonian and Laird’s variance estimator were used for meta-analysis.=0.075]. There was a significant reduction of FI prevalence in women post-bariatric surgery . There was a statistically significant reduction in FI prevalence following Roux-en-Y gastric bypass and one anastomosis gastric bypass . There was no significant reduction of incontinence episodes post-operatively . Quality of life (QOL) was not significantly improved post-bariatric surgery .Thirteen studies were included, eight assessing prevalence (678 patients) and 11 assessing severity of FI (992 patients). There was no significant difference in prevalence post-operatively overall, though it trended towards a reduction [pooled OR=0.55; There was a significant reduction in FI prevalence in women and those who underwent Roux-en-Y or one anastomosis gastric bypass. Our results for FI prevalence overall, FI severity and impact on quality of life were not statistically significant. Larger studies are needed in this under-researched area to determine the true effect of bariatric surgery on FI.The online version contains supplementary material available at 10.1007/s11695-021-05360-7. FI is defined as the involuntary loss of liquid or solid faeces and, in some definitions, includes the loss of gas. Contributing factors include older age, female sex, an obstetric history, colorectal surgery and anorectal disease . It is a2O per kg/m2 unit of BMI )  . All eight studies used a validated questionnaire to assess the severity of FI pre- and post-bariatric surgery. Three papers used the Faecal Incontinence Quality of Life Scale (FIQL) questionnaire, two used Gastrointestinal Quality of Life Index (GIQLI), two used the Wexner Scale, and one used PFDI-20. Five studies assessed pre- and post-operative frequency of FI episodes and found that frequency of incontinence episodes reduced post-operatively, though this was not a significant result  Fig. . There wp=0.007] , p=0.073, respectively].Of the 678, 390 (58%) underwent Roux-n-Y gastric bypass or mini-gastric bypass, 190 (28%) had gastric banding, 141 (21%) had laparoscopic or open sleeve gastrectomy, and 29 (4%) had a duodenal switch. There was a statistically significant reduction in FI prevalence following Roux-n-Y or one anastomotic gastric bypass . The difference in the frequency of FI pre- and post-bariatric surgery was also not statistically significant. We assessed the effect of faecal incontinence on quality of life, across areas of behaviour change, depression, impact on lifestyle and feeling of embarrassment. We found no statistically significant difference pre- and post-operatively in these areas.This systematic review summarizes and reports available evidence on the effect of bariatric surgery on FI. For women, we found a statistically significant reduction in FI pre- and post-surgery . There was also a statistically significant reduction in patients after Roux-n-Y gastric bypass or one anastomosis gastric bypass. While there was a trend towards less FI following bariatric surgery among patients, this did not reach statistical significance [OR 0.55; CI 0.28 to 1.06; Faecal incontinence has important clinical and psychosocial consequences. It may contribute to loss of independence and significant psychosocial stress. Compounding this, it is currently underreported and likely underappreciated as a symptom . For cliOur study found a statistically significant reduction of FI after Roux-en-Y gastric bypass and one anastomosis gastric bypass. This could be because Roux-en-Y represented the most common surgery in our studies, hence had the most power to reveal a significant result. Alternatively, Roux-en-Y gastric bypass may be particularly effective at reducing FI possibly through greater weight loss. We did not, however, find a statistically significant correlation between the reduction in BMI and reduction of FI, so there may be other hidden factors.Though our conclusion regarding FI severity is limited by the heterogenous data, some insights can be gained from the included studies. The largest study that assessed quality of life after FI, Elias et al., looked at 208 men and women and found a statistically significant improvement in lifestyle, coping and behaviour and embarrassment after bariatric surgery . Though We were not able to assess the pathophysiological factors that may be driving the reduction in FI after bariatric surgery. The literature suggests that obesity may increase intra-abdominal pressure and deplete the anal sphincter’s ability to remain continent. This evidence is particularly present in women, and thus reduced intra-abdominal and thus anal sphincteric pressure may explain the findings of our systematic review. However, our study showed that there is an improvement in FI after bariatric surgery independent of weight loss. We postulate that there are hidden factors driving the benefit of bariatric surgery on FI in women and gastric bypass patients.p=0.04) in men and women after bariatric surgery. Diet is another important factor [We did not find an improvement in FI for men, or for patients undergoing other operations other than Roux-en-Y or one anastomosis gastric bypass. There were a small number of men and surgical procedures outside of gastric bypass in our study, so the study was perhaps not powered to detect these changes. In these patients, there may also be factors that are counteracting the benefits seen in women and bypass patients. Stool consistency is also an important determinant of continence. Elias et al. found a significant change in stool towards a looser consistency


Klebsiella pneumoniae, an opportunistic pathogen is a leading cause of neonatal sepsis. The success of K. pneumoniae as a pathogen can be attributed to its multidrug-resistance and hypervirulent-pathotype. Though the WHO still recommends ampicillin and gentamicin for the treatment of neonatal sepsis, K. pneumoniae is rapidly becoming untreatable in this susceptible population. With escalating rates of cephalosporin use in health-care settings, the increasing dependency on carbapenems, a “last resort antibiotic,” has led to the emergence of carbapenem-resistant K. pneumoniae (CRKP). CRKP is reported from around the world causing outbreaks of neonatal infections. Carbapenem resistance in CRKP is largely mediated by highly transmissible plasmid-encoded carbapenemase enzymes, including KPC, NDM, and OXA-48-like enzymes. Further, the emergence of a more invasive and highly pathogenic hypervirulent K. pneumoniae (hvKP) pathotype in the clinical context poses an additional challenge to the clinicians. The deadly package of resistance and virulence has already limited therapeutic options in neonates with a compromised defense system. Although there are reports of CRKP infections, a review on neonatal sepsis due to CRKP/ hvKP is scarce. Here, we discuss the current understanding of neonatal sepsis with a focus on the global impact of the CRKP, provide a perspective regarding the possible acquisition and transmission of the CRKP and/or hvKP in neonates, and present strategies to effectively identify and combat these organisms.The convergence of a vulnerable population and a notorious pathogen is devastating, as seen in the case of sepsis occurring during the first 28 days of life . Sepsis leads to mortality, particularly in low-income countries (LICs) and lower-middle-income countries (LMICs).  The infiltration of sterile regions of the body with microorganisms and the manifestation of a reaction to it thereof, is known as sepsis. When this occurs within the first 28 days of life consequences can be dire, as the newborns first encounter a world of pathogens. Their immune system has not yet developed to equip them in this battle. Thus, the total number of neonatal deaths due to sepsis is a staggering half-million per year , 2.The pathogens that a neonate encounters are essentially present everywhere, starting with the birth canal, the crib, the hands of the nurse, or even the nasogastric tube. For the ones who are premature or low-birth-weight and require prolonged hospitalization or life support systems, the chances of infection are very high . In low-Klebsiella pneumoniae  are also resistant to several other antibiotics. Carbapenem-resistant genes are frequently harbored on plasmids that can spread from one species to the other. These resistance genes code for enzymes that efficiently hydrolyze carbapenems and all other β-lactam antibiotics. Further, most are also resilient against inhibition by the commercially viable β-lactamase inhibitors. In addition to carbapenem resistance, K. pneumoniae also had another ace up its sleeve, hypervirulence. Hypervirulent K. pneumoniae (hvKP) possess features that arm them to evade the host immune system to cause infections in immunocompetent hosts. hvKP are invasive and can disseminate to multiple sites.If one had to name an organism that readily becomes resistant to antibiotics, can harbor numerous plasmids, can survive in the environment & within the human gut, and is a dread in the neonatal intensive care units (NICU) in LMICs, it would be none other than eumoniae , 5. ThisWith the World Health Organization (WHO) guidelines of treatment inadequately poised to tackle CRKP and hvKP in the neonatal population, this review presents different aspects of CRKP and hvKP and their impact on the newborn.According to the “Levels and Trends in Child Mortality report, 2019” the estimated global rate of neonatal deaths was 17 per 1,000 live births, and worldwide ~6,700 neonates died each day in 2019 , in which case, infections are conventionally thought to be transmitted from the mother. Any sepsis presenting after 72 h of life is defined as Late-onset sepsis (LOS) and the infection in such cases is thought to be hospital or community-acquired , 8. PremK. pneumoniae and Acinetobacter baumannii play a pivotal role in causing neonatal septicemia along with Escherichia coli and Gram-positive Staphylococcus aureus in resource-poor settings  tract of healthy human beings   , 25. Itss (ICUs) .K. pneumoniae is also the predominant causative pathogen of neonatal sepsis   , a method of distinguishing strains based on DNA sequences of internal fragments of multiple house-keeping genes, is prevalent. In nd tonB) . The extlsewhere . K. pneuntigens) .K. pneumoniae is essentially linked with its capsule which serves a dual purpose in the cell: it protects the cell from phagocytosis mediated by polymorpho-nuclear granulocytes and serum resistance by inactivation of one of the complement components (C3B). The pili or fimbriae is another component of the bacterial cell that helps in pathogenicity by mediating the adhesion of the pathogen to the mucosal layer and/or epithelial cells of the lower urinary tract, respiratory tract, and GI tract. Type 1 pili mediate adherence and then colonization of urinary and respiratory tract. Mannose-resistant Klebsiella-like hemagglutinin (MR/K-HA), a Type 3 pili, helps in the adhesion to Bowman's capsule, renal vessels, and tubular basal membranes of the human kidney (K. pneumoniae often possess large virulence plasmids (pLVPK) which harbor rmpA, rmpA2, and aerobactin biosysnthesis genes , transposons , and integrons , present in the plasmids, mediate mobilization of the resistance genes (often gene cassettes) between different plasmids or between chromosome and plasmids  determinants are plasmid-mediated in eumoniae , 36. Mos E. coli . The seg E. coli . PCR-bas E. coli  and advaI2, IncL . One of eplicons . IncFIIKeplicons . Apart fplasmids .K. pneumoniae emerged and spread throughout the world  producing he world , 40. Thieumoniae . Eventua in 1991 . KPC-1-p in 1996 . This caorldwide , 44.K. pneumoniae or other bacteria occurs by two main mechanisms: (i) production of carbapenemases  which hydrolyze oxacillin, cloxacillin, and carbenicillin, are inhibited in vitro by NaCl , class B , and class D  of β-lactamases according to the Ambler classification. Molecular class A and D enzymes are called serine carbapenemases as they contain serine molecule in their active site and molecular class B enzymes are called metallo-β-lactamase (MBLs) as they contain two Zn by NaCl . As diff by NaCl . All sucblaKPC gene is found within a unique transposon Tn4401 variant which has led to the mobilization of the gene to different types of plasmids and through the plasmids to other organisms (https://www.ncbi.nlm.nih.gov/pathogens/refgene/#blaKPC), of which KPC-2 and KPC-3 are prevalent. Association of the KPC-2 and KPC-3 with epidemic clone ST258 is the pivotal factor for the spread of these genes.KPC is a plasmid-mediated molecular class A serine carbapenemase. rganisms . This carganisms , and therganisms . CurrentK. pneumoniae and E. coli in 2009 and was recovered from a Swedish patient returning from India (blaNDM reported in the NCBI pathogens database (https://www.ncbi.nlm.nih.gov/pathogens/refgene/#blaNDM). blaNDM is found across various sequence types of K. pneumoniae, no association with any particular ST was reported , qnrB, qnrS, aac(6′)-Ib-cr (plasmid-mediated fluoroquinolone resistance), and blaCTX−M−15 (ESBL)   and a bleMBL gene (downstream)  is the most widely disseminated class B metallo-β-lactamase. It was first reported in a om India . Althougom India , 52. Curreported . Co-exis5 (ESBL) , 28, 54 M/FIB-M) . The blanstream) .K. pneumoniae isolate which possessed MBLs and lacked outer membrane proteins  are spread in Southern Europe and also in other countries  carbapenemase was first reported in the year 1991 from Japan from an s strain . Followeountries . VIM-1 an Greece . Both thVarious studies have been published regarding the spread of carbapenem-resistant Enterobacteriaceae but the data on neonatal sepsis is infrequent. Here we present the studies related to neonatal sepsis caused by CRKP . We haveK. pneumoniae have been reported in neonates from various countries such as Egypt -Ib-cr, qnrB, and qnrS. The genetic environment of blaKPC−2 in ST147 strains from India corroborated with the genetic environment of the other blaKPC−2-possessing strains recovered from adults, where blaKPC−2 was associated with IS elements ISKpn6 and ISKpn7, plasmid type IncFII, and transposon Tn 4401. All neonates in this study had an overlapping stay in the hospital so a chance of transmission from one neonate to another was predicted  , qnrB, qnrS, aac(6′)-Ib-cr (plasmid-mediated fluoroquinolone resistance), blaCTX−M−15 (ESBL)  . These i5 (ESBL) , 28, 86 X3, etc. .blaNDM−1 have also caused outbreaks in several healthcare settings. During August 2011–Jan 2012, an outbreak occurred due to K. pneumoniae ST1043 in a neonatal unit in Colombia infecting six neonates. As the neonates had no contact with people from countries that reported NDM-1-producing bacteria, the authors proposed that autochthonous clones were acquiring the blaNDM gene  and ST888 (n = 1), which were susceptible to gentamicin, amikacin, aztreonam, ciprofloxacin, and levofloxacin. NDM-1-producing ST20 strains (n = 2) were also isolated from the hospital environment  were found colonizing the gut of the neonates in two maternity wards. Carriage of carbapenem-resistant strains was significantly related to the low-birth-weight of the neonates . However, since the mid-1980s, the emergence of hypervirulent K. pneumoniae (hvKP) in the clinical context poses a far greater challenge to the clinicians , regulator of mucoid phenotype A (rmpA) genes, biosynthetic genes responsible for the production of siderophore salmochelin (iro cluster), aerobactin producing biosynthetic genes (iuc cluster), virulence plasmid-encoded gene with unknown function (peg-344), and the virulence plasmid-encoded heavy metal resistance genes for tellurite (ter cluster) and silver (silS)  in the clinical context has identified a set of important and unique hypervirulent biomarkers which can accurately differentiate hvKP from cKP, including several capsular serotypes , mucoviscosity-associated gene A (r (silS) , 91, 106d to cKP . In the K. pneumoniae. Both cKP and hvKP possess chromosomally-encoded capsular polysaccharide (K antigens) genes, known as the cps cluster  and one is chromosomally-encoded (c-rmpA)  can induce the transcription of entire cps operon, resulting in hypercapsule production  . Severaloduction . In sepaor rmpA2 , 117. Ineumoniae , 119. Sus operon , 121.K. pneumoniae. However, this essential metal is not readily available in the host during the infection because of the non-specific immune response exhibited by the host where the host efficiently sequesters this metal ion (Fe3+) with several iron-binding molecules, such as transferrin and lactoferrin, eventually restricting the growth of many opportunistic pathogens  and salmochelin (iroBCDN), regulators of hypercapsule production , resistance genes for tellurite (terZABCDE and terWXY) and silver (silS)  and pLVPK  , 35. Allr (silS) . Recentlr (silS) . Similarr (silS) . The latSeveral studies showed that the genes conferring hypervirulence are widely distributed across diverse STs  but someK. pneumoniae that are both antimicrobial-resistant and virulent have surely put an end to this debate. K. pneumoniae are extremely capable of receiving and incorporating DNA segments from other bacteria, mostly via large plasmids  genes  genes , 134. On strains , 157.blaKPC−2-harboring CR-hvKP strains from China belonged to ST11. Although ST11 clone of K. pneumoniae is an internationally categorized high-risk clone known to harbor blaKPC−2 as the major carbapenemase gene, these recent studies have confirmed its association with the hypervirulence attributes.Since 2015, multiple epidemiological studies from China showed the prevalence of KPC-2-producing CR-hvKP strains in the clinical settings causing several infections in otherwise healthy individuals, including UTI, pneumonia, septicemia, bacteremia, abdominal infections, septic arthritis, catheter-associated bacteremia, and ventilator-associated pneumonia –142, 144in vitro and in vivo  have also been detected in hvKP strains. For example, a recent study from China showed the emergence of an ST86 CR-hvKP K2 strain that co-harbored two different classes of clinically important carbapenemase-producing genes blaNDM−1 and blaKPC−2. This strain was also responsible for significant mouse lethality  of ESBL-producing K. pneumoniae detected in the neonates were from the maternal gut flora  or EDTA (for MBLs)  .Colorimetric methods to detect carbapenemases directly from blood without blood culture are cost-effective and less time consuming (3–4 h). A study evaluated two variations of CarbaNP, CarbaNPT-direct which uses Triton X-100 as enzymatic extractor and Blue-carba which uses bromothymol blue instead of phenol red, for detection of carbapenemases directly from blood samples . The sturmpA and/or rmpA2-positive non-hypermucoviscous strains and also rmpA and/or rmpA2-negative hypermucoviscous strains were detected in causing invasive syndrome  using polymerase chain reaction (PCR). These hypervirulent biomarkers hold the promise of a sensitive and specific diagnostic test in future. Since, the methodology is largely genotype-based, it is restricted to the research laboratories and may not be readily available in the healthcare settings of LMICs. Research is on-going for the development of a cost-effective commercial test which will not only help the clinical laboratories but can also be used in surveillance and research studies  Working Group adopted a tool, AWaRe. This tool classifies the antibiotics into three groups:  Reserve . The Acc Reserve .For both early and late onset neonatal sepsis, the most commonly recommended and used antibiotics, as per the WHO guidelines, is a β-lactam antibiotic (most commonly ampicillin) combined with an aminoglycoside (most commonly gentamicin) . RecentlDue to the emergence and spread of CRKP strains in the healthcare settings, the treatment options for neonates are narrowing. Added to this, are the challenges in sepsis diagnosis. This alarming scenario demands new antimicrobials or additional alternatives for the treatment of CRKP-infected septicemic neonates. Although currently there is a scarcity of new antimicrobials globally, combination therapy is an alternative. Such therapies can expand the spectrum of antibiotic coverage and synergism between the antibiotics with enhanced killing effect. In addition, new alternatives have also been suggested for CRKP infections though all may not be suitable for neonates. For example, avibactam (a non-β-lactam β-lactamase inhibitor) showed high effectivity against KPC- and OXA-48-producing CRKP strains when combined with ceftazidime . SimilarK. pneumoniae to arrest their further dissemination.In response to the critical priority pathogens, recently WHO has published a third review of the clinical antibacterial pipeline where they enlisted a total of 8 new antibiotics that gained market authorization since July 2017 . Of themBifidobacterium spp., Bacteroides, Clostridium spp. and Lactobacillus spp. (in minor proportion)  , 200 andportion) . Whereasportion) . Pretermportion) , 200. Ifportion) . The useal death –201. Desal death , systemial death –205. Theed doses . As probK. pneumoniae in mice model  guidelines for the management of neonatal sepsis, which is currently ampicillin plus gentamicin, is in dire need of modification. The major burden of neonatal sepsis is borne by the LMICs where antibiotic resistance is high and microbiology laboratory support is inadequate. The number of documented neonatal infections caused by CRKP and hvKP are just the tip of the iceberg. Most cases are not recorded as the microbiology laboratories in resource-limited countries lack infrastructure and capability. This is probably likelier for hvKP, as these strains are not specifically detected in clinical microbiology laboratories. This lack of information is thus translated into treatment protocols. Studies have shown that the most severe forms of neonatal sepsis with an unfavorable outcome were due to virulent strains of eumoniae . The cliA recurring premise about carbapenemases is their ability to hydrolyze most β-lactam antibiotics, emergence of variants and their promiscuous nature. Plasmids are numerous and have facilitated intra and interspecies transmission of these genes particularly under antibiotic pressure. Globalization has encouraged their spread and most genes have within a few years of identification crossed boundaries and invaded new terrains. Clonal spread is uncommon but not unknown. The evolution of variants of enzymes that are more efficient or have better stability have also made them difficult to contain. Plasmids carrying carbapenem-resistant genes also carry other resistant genes in a bid to make a panel of antibiotics ineffective. With new carbapenem resistance genes being identified and new variants evolving, the problem of CRKP and hvKP that we recognize presently is incomplete.K. pneumoniae is that it commonly resides in the human gut. The rate of colonization of K. pneumoniae increases drastically in hospitalized patients with invasive devices, antibiotic exposure, and prolonged stay. Needless to say, that this would also happen with premature, low-birth-weight neonates with a pristine gut. K. pneumoniae that colonize the gut in the hospital are resistant to antibiotics and the gut provides an environment apt for the exchange of resistance genes. Studies have shown that such exchange of resistance genes frequently happen in the gut (K. pneumoniae was not only the predominant organism that colonized the neonatal gut, but also the most common organism isolated from the neonatal blood specimens (Another overlooked aspect of  the gut . Furtherpecimens . The excIt is difficult to change things overnight and the economic implications of these changes may also be a constraint on health systems that are poorly funded. The COVID-19 situation has further exposed the fragility of health systems around the world and newborns have also been affected. Measures that can reduce infection rates can also reduce CRKP and hvKP. These include surveillance systems to recognize changes in etiology and drug resistance profile, improved laboratories for better and timely detection of pathogenic strains, setting empirical treatment guidelines based on the profiles and proper education of mothers and healthcare workers regarding sanitation. We have come a long way from the days when we understood microbes through the lens of a microscope. We now seem to have an unprecedented power over them by being able to understand their genetic make-up to the last nucleotide. Whole genome sequencing has opened up newer avenues to understand the bacterial genomes. This enormous amount of information generated can be honed to create new cures and products. The challenge is big but there is light at the end of the tunnel.SB: conception, design, wrote the introduction, and discussion. SMu and SMi: performed literature search, wrote the initial draft, and prepared all the tables and figures. SB and SD: critically revised the manuscript. All authors read and approved the final manuscript.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.


Naturalistic functional magnetic resonance imaging (NfMRI) has become an effective tool to study brain functional activities in real-life context, which reduces the anxiety or boredom due to difficult or repetitive tasks and avoids the problem of unreliable collection of brain activity caused by the subjects’ microsleeps during resting state. Recent studies have made efforts on characterizing the brain’s hierarchical organizations from fMRI data by various deep learning models. However, most of those models have ignored the properties of group-wise consistency and inter-subject difference in brain function under naturalistic paradigm. Another critical issue is how to determine the optimal neural architecture of deep learning models, as manual design of neural architecture is time-consuming and less reliable. To tackle these problems, we proposed a two-stage deep belief network (DBN) with neural architecture search (NAS) combined framework (two-stage NAS-DBN) to model both the group-consistent and individual-specific naturalistic functional brain networks (FBNs), which reflected the hierarchical organization of brain function and the nature of brain functional activities under naturalistic paradigm. Moreover, the test-retest reliability and spatial overlap rate of the FBNs identified by our model reveal better performance than that of widely used traditional methods. In general, our model provides a promising method for characterizing hierarchical spatiotemporal features under the natural paradigm. Neuroscientists have long realized that functional brain networks (FBNs) present varying degrees of activation responses in a multi-scale hierarchical structure . In the In previous studies, a variety of conventional methods for modeling fMRI data to reconstruct and characterize FBN have been developed, such as general linear model (GLM) , indepenHowever, although these models have exhibited performance in extracting hierarchical spatiotemporal features of fMRI data at multiple scales, there still remain big challenges in such deep leaning models. Firstly, due to the high dimensionality of fMRI data and a variety of training parameters, manual design of neural architecture depending on experience is very time-consuming and less reliable. Hence, it is necessary to develop computational framework for automatic construction of optimal neural architecture (NA) for FBNs construction models. Recently, there have been some literature studies that successfully applied neural architecture search (NAS) framework to fMRI data for brain network modeling ,c. For iSecondly, various research studies have demonstrated the intrinsic properties of neural process under naturalistic paradigm, that brain responses evoked by this condition exhibit highly consistency across individuals, but also show great inter-subject variability, especially in heteromodal association cortices , which rThe computational framework of two-stage NAS-DBN is illustrated in Seventeen right-handed healthy subjects participated in the study. During scan, participants freely watched a 20-min movie named “The Butterfly Circus,” which depicts a story of a man born without limbs who is encouraged by a famous circus performer to discover his potential. All the subjects signed a written informed consent and reported that they had not previously seen the movie. The experiments were composed of two scanning sessions with a 3-month interval, where all the subjects watched the same movie in each session . We mark3 isotropic voxels. The preprocessing pipeline was conducted by Statistical Parametric Mapping toolbox (SPM12), including slice timing correction and motion correction, co-registration, normalization to 2 mm MNI152 standard template , spatial smoothing with 6 mm full width half maximum Gaussian kernel, band pass filtering (0.0085 ± 0.15 Hz), and masking. The fMRI signals of each subject contain 530 volumes. Whole-brain fMRI signals of each subject were extracted and stacked into a 2D matrix Sx , where each column represents the fMRI signals of each voxel. In addition, fMRI time series of each voxel were normalized to have zero mean and unit variance. We concatenated all individual subjects’ fMRI time series to a group-wise matrix for group-level DBN training.fMRI images were acquired from a whole-body 3T Siemens Trio MRI scanner with following scanning parameters: TR = 2,200 ms, TE = 30 ms, FA = 79°, FOV = 134 mm × 134 mm, a 64 × 64 acquisition matrix, 44 axial slices, and 3 mmAs the particle swarm optimization algorithm (PSO) owns multiple advantages , includih and I represents current iteration/generation; w is the inertia weight; c1and c2 are constant real values; Rand1 and Rand2 are random real numbers; In Equations (1) and (2), us study . Due to v and hidden layer variable h, of which energy function is as follows:In general, DBN is composed of multiple stacked Restricted Boltzmann Machines , which mvi and hj represents the activation state of two layers; bi and bj indicate their bias; wij is the weight between two layers. In this work, the DBN model with the optimal NA was applied to define the architecture of DBN model, aiming to characterize the two-stage hierarchical FBNs and corresponding temporal features. In the first stage, the optimized DBN was adopted to model group-level NfMRI data to train a weight matrix from each layer as Wi ∈ Rkt×m, which represents the group-wise temporal features. Specifically, all the individual fMRI signals were concatenated along the time to a group-level NfMRI matrix for first-stage training. In the second stage, the subject-specific DBN models were applied to each individual NfMRI matrix to further identify individual-level temporal features and FBNs while maintaining their correspondence across subjects. To achieve this, the group-level weight matrix Wi of each layer derived from first stage was used to initialize the subject-specific DBN model. In general, according to previous FBNs identification literatures , our model overcomes the weakness of these shallow models in terms of extracting the complex interactions between brain regions and the hierarchical organization of FBNs. Thus, to evaluate the performance of the proposed two-stage DBN model, we compared it to ICA and SDL in terms of modeling fMRI time series to construct FBNs. Both group ICA and SDL were applied to spatial-concatenated group-wise NfMRI signals of all the subjects. Specifically, SDL was implemented by effective online dictionary learning method via a public softwarematrix A . Note thmatrix A , which dmatrix A . For farTo evaluate the performance of three models in terms of effectiveness of constructing spatial patterns, quantitatively, we compared the spatial similarity between spatial patterns (FBNs) derived by these models and the well-established RSNs, where the spatial pattern overlap rate O is defined aswhere S is the FBN identified by these methods and T is the RSN template, respectively.i is defined as following equation.To investigate the hierarchical organization of temporal responses derived from proposed framework, we calculated the inter-subject correlation (ISC) using individuals’ temporal responses extracted from weight matrix of DBN model, where ISC measures the inter-subject consistency for temporal responses of each atom from each hidden layer across individuals . Specifirij represents the Pearson correlations between the temporal response corresponding to one atom in one subject i and that temporal responses in each of the remaining subjects j in the group. This ISC analysis was conducted for each atom of each hidden layer for all the subjects, separately. We then derived the ISC metric for each layer and each subject by averaging the ISC values across all the atoms belonging to the same layer, respectively. Moreover, the group-level ISC metric was derived by averaging all the individual’s ISCs for each layer, respectively.Where To test the reproducibility of each brain network measures derived from our model and commonly-used methods, we conducted the same two-stage DBN, group-wise SDL and ICA on fMRI dataset of session B, and detected matching FBNs, which share maximum number of overlapping voxels with FBNs derived from session A. In addition, further careful manual inspection was conducted to verify the matching FBNs of the two sessions. Then, we calculated test-retest reliability of each selected matching FBNs. The reliability is quantified by calculating the intra-group correlation coefficient (ICC) between two datasets , which iThe details of this procedure were accomplished according to our previous study . We evalTo quantitively evaluate the effectiveness and reproducibility of NAS framework and obtain the reliable optimal architecture of DBN model, we independently performed 10 times of NAS processes. Considering subjects and stimuli of the two sessions are the same, we only used 17 individuals of session A as training dataset for NAS procedure.–7. These experimental results show the robust superiority of our NAS framework. Afterward, we averaged 10 NAS results, thus determining that the optimal architecture of DBN model has 3 layers and 184 neurons, which was further used for characterizing both group-level and individual-level hierarchical FBNs on session A and session B separately.For the 10 results of NAS, the numbers of neurons were in range from 170 to 200, and layers were always 3, showing high consistency and robustness . The rec2 and ran on a deep learning server with GeForce GTX 1080 TI. The NAS process was accomplished on one GPU card within acceptable time (8 h).For the hyperparameters of two-stage DBN model, as each individual NfMRI signal has 530 volumes, the number of visible units of group-level DBN model in the first stage is 9,010 (530 × 17) for both session A and session B. In addition, the number of neurons and layers in the first-stage DBN were determined according to results of NAS. The target sparsity (the ratio of active hidden units) and learning rate in the first/second/third hidden layer were set as 0.01/0.05/0.05 and 0.001/0.001/0.001, respectively, and the batch size was set as 10. The model converged after approximately 50 epochs. In the second-stage, the individual DBN model was applied to 17 subjects with 530 visible units, separately. The hidden units and other hyperparameters set in the second stage of DBN were set as same as the first stage. In addition, all the experimental results were run on both session A and session B, including group-level and individual-level FBNs identification, ISC analysis of temporal features, and spatial/temporal hierarchy analysis. As two sessions yielded similar results, we thus mainly presented results based on session A in the main text, and results based on session B in the supplementary results as a further validation –5. The cAfter the specification of the model architecture, we further explored the hierarchical FBNs during movie viewing defined by the our two-stage NAS-DBN framework. We first selected and showed some representative hierarchical group-level FBNs identified in the first stage DBN. Some well-known brain networks can be successfully identified , includiWhile naturalistic stimuli can trigger highly consistent neural responses in primary sensory areas, neural activities evoked by this condition especially in the higher-order heteromodal cortices also show great inter-subject variability, which can be modeled by our individual-level DBN model with cross-subject correspondences kept by group-level DBN model. To further verify the correspondence of group-level and individual-level FBNs, we randomly selected and compared representative group and individual FBNs in an exemplar subject, including three visual networks, auditory network, default mode network, sensorimotor network, dorsal attention network, executive control network . SpecifiDBN model consists of multiple stacked RBM block, which makes it a feature extractor to capture the hierarchical temporal and spatial features from NfMRI data. In general, the hierarchical temporal features can be derived from weight matrix and the associated spatial features can be represented by the output of each hidden layer of DBN model, respectively. Specifically, our two-stage NAS-DBN framework can not only characterize hierarchical temporal responses, but also reveal the meaningful group-level and individual-level FBNs with hierarchical organization.First, to investigate the hierarchical organization of temporal responses derived from proposed framework, we measured and compared the inter-subject correlation (ISC) of individuals’ temporal responses, at both individual-level and group-level. We averaged the ISC metrics for each layer at individual-level and group-level, respectively, the lower layer temporal responses show less inter-subject consistency, while higher layer temporal responses show higher consistency across individuals at both individual-level and group-level , which rSupplementary Figure 2In addition, Inspired by this, as our proposed model characterized group-level and individual-level FBNs with good correspondence, we further calculated the average ISC values derived from all the individual temporal features corresponding to each FBN illustrated in NL)(and a higher layer space maps NH) between a lower layer spatial maps t-test, p < 10−307), which indicates that FBNs in higher layer show more complexity and richness, further suggesting the existence of hierarchical structure of FBNs under naturalistic condition.We first calculated ISR metric for FBNs derived from first-stage DBN model for session A and session B, respectively. As two sessions yielded similar results, results for session B were listed in t-test, p < 10−11). In general, these ISR maps between associated networks and temporal features between different layers quantitatively confirmed the hierarchical organization of spatial distributions and temporal features, further suggesting the superiority of our proposed model in modeling meaningful spatiotemporal features under naturalistic condition.Moreover, we further calculated ISR metrics for temporal responses derived from first-stage DBN model between adjacent layers for session A and session B, respectively. As two sessions yielded similar results, the results of session B were listed in Finally, to evaluate the performance of the proposed two-stage DBN model, we compared it to widely used data-driven methods, ICA and SDL, in terms of overlap rate with RSN template and test-retest reliability of FBNs. As shown in t-tests with multiple testing corrections to ICCs of each representative network, respectively. Consequently, except that the ICCs of auditory network derived from layer1 of the proposed model are significantly lower than that derived from SDL (FDR-corrected p < 0.001), the ICCs of all the other networks derived from the proposed model are significantly higher than that derived from ICA and SDL methods (FDR-corrected p < 0.001), indicating the superiority of proposed model in characterizing spatial patterns with good long-term reliability under naturalistic paradigm (Afterward, we would like to evaluate the long-term test-retest reliability of our method. Two-stage NAS-DBN, group ICA and SDL were employed to identify FBNs in the repeated scan sessions. To compare the test-retest reliability of these methods, we focused on three networks that can be defined in both sessions by all three methods, including visual network, auditory network and default mode network. We assessed the voxel-wise ICC of each FBN, where all three methods showed a range of reliability at the voxel level across different networks . Specifiparadigm .In this study, we proposed a two-stage NAS-DBN framework to derive group-level and individual-level spatio-temporal patterns from NfMRI signals, offering one of the first applications of NAS-DBN framework for analyzing dynamic naturalistic fMRI data. The advantages of our framework are summarized as follows. First, based on PSO, our NAS framework can find feasible optimal solution for neural architecture of DBN within acceptable time with limited computing resource. In addition, according to previous NAS-vs. DBN study , employiThe original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of the University of Queensland. The patients/participants provided their written informed consent to participate in this study.YR contributed to the conception and design of the study. YR, SX, and ZT drafted the manuscript and performed the research. LS and SX contributed to analyzing the data. XH contributed to supervision, writing-review, and editing. All authors contributed to the article and approved the submitted version.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.