Sustained neural activity during the delay phase of spatial working memory tasks is compelling evidence for the neural correlate of active storage and maintenance of spatial information, however, it does not provide insight into specific mechanisms of spatial coding. This activity may reflect a range of processes, such as maintenance of a stimulus position or a prepared motor response plan. The aim of our study was to examine neural evidence for the use of different coding strategies, depending on the characteristics and demands of a spatial working memory task. Thirty-one  and 44  participants performed a spatial working memory task while we measured their brain activity using fMRI in two separate experiments. Participants were asked to remember the position of a briefly presented target stimulus and, after a delay period, to use a joystick to indicate either the position of the remembered target or an indicated non-matching location. The task was designed so that the predictability of the response could be manipulated independently of task difficulty and memory retrieval process. We were particularly interested in contrasting conditions in which participants (i) could use prospective coding of the motor response or (ii) had to rely on retrospective sensory information. Prospective motor coding was associated with activity in somatomotor, premotor, and motor cortices and increased integration of brain activity with and within the somatomotor network. In contrast, retrospective sensory coding was associated with increased activity in parietal regions and increased functional connectivity with and within secondary visual and dorsal attentional networks. The observed differences in activation levels, dynamics of differences over trial duration, and integration of information within and between brain networks provide compelling evidence for the use of complementary spatial working memory strategies optimized to meet task demands. For example, Curtis et al.  used funmatch condition required maintenance of the precise target position and its successful recall, correct performance in the non-match condition required only a coarse representation of the target position and its successful recognition. A subsequent study by Srimal and Curtis , we used a full factorial design with independent manipulation of response predictability and task difficulty. In the second experiment (Experiment II), we focused on response predictability in conditions of precise spatial recall only. In both experiments, we expected that retrospective sensory coding would be reflected in increased activity and connectivity in parietal and posterior sensory areas, whereas prospective motor coding would be associated with increased activity and connectivity in frontal areas involved in motor planning and execution. In addition, we expected that differences in strategies would be time-dependent, with earlier phases of the delay period reflecting preparation of a prospective motor plan and later phases of the delay period reflecting maintenance and reactivation of retrospective sensory information.d = 0.5) at p < 0.05 with 0.8 and 0.9 power in Experiments I and II, respectively. All participants were healthy young adults with no current or previous neurological, psychiatric, or substance use disorders. Exclusion criteria also included any contraindications to MR or EEG, such as the presence of metal implants or other metal particles in the body, a history of epileptic seizures, tremor, or other motor disorders, and pregnancy. All participants had normal or corrected-to-normal vision. Participants performed the task with their dominant hand, with the majority of participants being right-handed and only two participants being left-handed (Experiment I). Due to the small number of left-handed participants, we decided to exclude these participants to ensure a homogeneous sample. In addition, we excluded 13 participants due to incomplete data collection and poor data quality . Demographics of participants included in the data analysis can be found in Thirty-one  and 44  participants took part in two spatial working memory experiments. The number of participants was selected to exceed sample sizes of comparable fMRI studies on spatial working memory  but at a random angle to the target position, excluding any locations that were too close to the screen edges . In the match and non-match conditions, two red disks  appeared on the screen during the response period. One of the disks appeared at the position that matched the target position, while the other disk appeared at the same amplitude from the center 50° (30° for only one participant) clockwise or counterclockwise from the target position. The position of the non-match target varied in a pseudorandom manner and was counterbalanced across the trials. The gray response disk was presented at the same time in the center of the screen. In the match condition, the response disk had to be placed over the red disk at the position that matched the target. In the non-match condition, participants had to place the response disk over the red disk at the position that did not match the target position.The task consisted of four conditions—center and off-center conditions to encode and recall spatial information using a high-precision representation, whereas in the match and non-match conditions they could rely on coarser spatial encoding and recognition that allowed match-to-sample responses. In this way, we were able to contrast conditions with different representation requirements at different task difficulty levels. In the off-center and non-match conditions, the required motor response was not known prior to the onset of response period, since the response either began or ended at random, unpredictable locations, respectively. Importantly, the prospective motor coding in these two conditions was not only uninformative but also misleading, as it interfered with the actual motor response that participants were required to make. We hypothesized that this would discourage participants from creating a prospective motor plan and instead encourage them to rely solely on retrospective sensory representations. The reverse, however, was not true in the center and match conditions. In the center and match conditions, the required motor response was known at the time of target presentation, allowing participants to complete the task by using either retrospective sensory coding, prospective motor coding or both coding strategies.In summary, the task design required participants in the center, match, non-match, off-center, off-center, non-match, match, and center. The order was chosen to counterbalance the effects of training and fatigue across task conditions and to group responses of the same type . Each run consisted of 18 trials, yielding 36 trials per condition and 144 trials in total.The data in Experiment I was collected in a single session. Participants first performed a short practice to familiarize themselves with the task and the use of joystick. During the practice, we described the task conditions and the required responses. Participants then performed the task while their brain activity was observed using fMRI recording. The task was performed across eight scanning runs. To enable and encourage the use of a stable strategy, each run included only one task condition  from the target position but at randomly varying angles from the target position, excluding positions that were too close to the screen edges .In this experiment, the timing and duration of various phases of a task trial remained the same as in the first experiment with the exception of the ITI durations, which were varied pseudorandomly between 15, 16, or 17 s with a ratio of 3:2:1. The target stimulus  was presented at 24 different positions from 7.5 to 352.5° in 15° increments. In the The data for Experiment II was collected over one to three sessions . On each individual session, after training, the participants performed the task in two separate runs during which concurrent fMRI and EEG signal was recorded. Each run consisted of 24 trials of the same task condition, resulting in 24, 48, and 72 trials per condition, 48, 96, and 144 trials in total, for one, two, or three sessions, respectively. In the first session, the order of task conditions was pseudorandomly varied and counterbalanced across participants. In each subsequent session with the same participant, the order was reversed from the previous session. Data from participants who attended multiple sessions were combined across sessions. In this article, we report results based only on behavioral and fMRI data. While EEG data are not the focus of this paper, we used EOG signal to identify eye movements during task performance.center condition and 11.1%  of trials during the off-center condition. Using logistic regression to test for differences between task conditions, we found no evidence of systematic differences in saccade frequency between task conditions .In Experiment II, we used the electrooculography (EOG) signal extracted from the EEG data to check whether participants followed instructions and avoided eye movements during the presentation of the target and the delay phase of the spatial working memory task. Details of EEG data acquisition and EOG analysis can be found in the Invivo, 2012, monitor size: 640 × 400 mm) that was visible to participants from the MR scanner via a head mirror . The task was prepared using a custom Python script and the PsychoPy software . For the center and off-center conditions, we used several criteria to identify outliers. First, any response that was more than 45° from the target position in either direction or whose amplitude was not between 0.5 and 1.75× target amplitude was excluded from further analysis. Due to the potentially large impact of outliers, we additionally excluded all responses that fell outside the 1.5× IQR boundaries for either angular or amplitude error .To standardize the behavioral measurements across different screen resolutions and viewing distances, we first converted the pixel-based measurements to degrees of visual angle. We then excluded all invalid responses and outliers to ensure that the results reflected the engagement of spatial working memory, rather than technical errors or inattention to the task. For the match and non-match conditions, we computed error rates as the proportion of trials in which participants did not correctly place the response disk to overlap the red disk at the position that matched the target or the red disk at the alternate position, for match and non-match conditions, respectively. We tested the difference in error rates between match and non-match conditions by computing a logistic regression model with the task condition as a predictor and testing its statistical significance with a Z-test.Next, we examined task performance in each task condition. For all conditions, we used the final position of the response disk as the participant's response. For center and off-center conditions, which required precise reconstruction of the target position, we used the final position of the response target relative to the target position to assess the precision of the behavioral responses. As findings from single-neuron recordings suggest that at the neuronal level spatial representations are encoded in terms of an angle and an amplitude, in other words in the polar coordinate system  and paired In both experiments, MRI data were collected with Philips Achieva 3.0T TX scanner. T1- and T2-weighted structural images were acquired for each participant . We recorded brain activity using BOLD images with T2*-weighted echo-planar imaging sequence .MRI data were preprocessed and analyzed using Quantitative Neuroimaging Environment and ToolboX  FWE correction. To identify regions activated across pairs of conditions, we performed a conjunction analysis  or in at least one of the task conditions (u = 1). Multiple comparison corrections were performed using FDR and results were thresholded at q < 0.05. To identify differences between task conditions based on the dense data, we performed two-tailed paired t-tests with cluster size (C = 3.1) FWE multiple comparison correction. Permutation tests and multiple comparison correction were performed independently for left cortical surface, right cortical surface, and subcortical volume. To maintain whole-brain Type-I correction at .05, we set the threshold for the corrected p-values to p < 0.017. For group-level analysis on the parcellated data, we performed two-tailed one-sample t-tests with FDR correction to identify activation and deactivation during individual events. We also compared task conditions by performing two-tailed paired t-tests with FDR multiple comparison correction. The resulting images were thresholded at q < 0.05.We then analyzed the β estimates at the group level using permutation analysis . To identify activation and deactivation during individual events based on the dense whole-brain data, we performed two-tailed one-sample For the functional connectivity analysis, data were additionally processed to identify frames with excessive motion and associated signal artifacts and to remove nuisance signal. Specifically, we identified any frames in which motion exceeded 5 mm frame displacement or signal change was >1.6× the median of the normalized frame-to-frame root-mean-squared differences (RMSD) in voxel intensities. Identified frames were linearly interpolated before high-pass filtering (0.008 Hz) and excluded from further processing and analysis. We used a GLM approach to estimate the signal contributions from motion parameters, ventricular and white matter signal, global signal, and the first derivative of all the nuisance signals. To prevent systematic inflation of functional connectivity estimates due to task response  and FDR correction for multiple comparisons and presented results that exceeded the significance threshold of q < 0.05. This approach allowed us to focus our investigation specifically on delay-related functional integration across multiple ROIs and networks. The obtained estimates of functional connectivity reflect the frame-to-frame covariation of the BOLD signal during the information maintenance task phase after accounting for the mean task response, while also minimizing systematic effects due to motion and nuisance signals.In the functional connectivity analyses, we focused on comparisons between pairs of task conditions across HCP parcels that were either identified as significantly activated during at least one of the task conditions or showed significant differences between these task conditions. We assigned parcel network membership based on the Cole-Anticevic Network Parcellation  as a fixed and participants as a random factor to predict error rates. While we observed slightly higher error rates in the non-match compared to the match condition .To test for possible differences in task difficulty due to manipulation of response predictability, we focused on error rates as a measure of behavioral performance under the tion see , a Z-tescenter and off-center conditions allowed the assessment of more precise measures of response accuracy. Specifically, we calculated response accuracy as the standard deviation of the corrected angular and amplitude errors. In Experiment I, the permutation-based t-test revealed a significant difference between task conditions in the angular error, t(22) = 2.80, p = 0.022, d = 0.503, reflecting slightly lower angular precision in the off-center condition (t(22) = 0.642, p = 0.529, d = 0.137. In contrast, the permutation-based t-test in Experiment II revealed a significant difference between task conditions in the amplitude error, t(36) = 3.55, p = 0.002, d = 0.455, reflecting lower precision in the amplitude of the response in the off-center condition (t(36) = 1.18, p = 0.256, d = 0.158.The ondition , but notondition , but notcenter and off-center conditions revealed consistent systematic effects on response errors. Specifically, individual participants tended to either undershoot or overshoot their responses, which we estimated as a measure of systematic amplitude bias  = 1.02, p = 0.318, d = 0.163; Experiment II: t(36) = 0.328, p = 0.743, d = 0.031. We tested the differences in angular bias with a repeated-measures ANOVA with factors task condition (center vs. off-center) and target angle from the nearest diagonal . The results showed a significant effect of the target angle from the nearest diagonal on angular bias in both experiments, Experiment I: F = 23.8, p < 0.001, F = 93.3, p < 0.001, F = 0.640, p = 0.263, F = 1.48, p = 0.068, F = 1.26, p = 0.288, F = 0.716, p = 0.488, Analysis of behavioral responses during ude bias . We alsoude bias . To asseions see , Experimonal see . Howeverp-values from statistical maps across pairs of images with the same task type within the same experiment. Specifically, we identified grayordinates that showed a robust response in both task conditions (u = 2) as well as those that showed a significant response in at least one of the conditions (u = 1) at the FDR whole-brain corrected criterion for statistical significance q < 0.05. This resulted in three separate maps showing regions that robustly responded during the delay period in (i) match and/or non-match conditions in Experiment I  ceriment I , and , two (u = 2), or all three (u = 3) conjunction maps, and identifies a number of brain regions and systems that show robust delay-related responses in all conditions (u = 3). Specifically, increased activity was consistently observed in the somatosensory, motor, and premotor cortices. The superior and inferior parietal cortex, as well as several areas in the prefrontal and inferior frontal cortex, also showed consistent delay-related activation. Higher activity was also observed in the cingulate, insular, and opercular cortex, as well as in several higher visual areas. Subcortical activation was observed in the cerebellum , sensory-visual, and association areas  in the identified differences of brain responses (see Direct comparison of difference maps across task types and experiments indicated moderate to large similarities (match and non-match conditions and (ii) center and off-center conditions in Experiment I and (iii) center and off-center conditions in Experiment II.Different coding and representation strategies may be associated with different temporal progression during a working memory trial. To observe temporal progression of the differences in delay-related response, we modeled the delay activity as two separate events. We modeled the first half of the delay period as early delay and the second half of the delay period as late delay see . We thenmatch and non-match conditions in Experiment I  in the early and moderate to large similarities (r = 0.30–0.48) in the late delay phases , and another that prevented the use of prospective motor codes and forced participants to rely solely on retrospective sensory information (non-match or off-center condition). We found that this manipulation of strategy use was reflected in brain activity. In general, somatomotor, premotor, and motor areas were more active when participants were able to use motor representations, whereas somatomotor and parietal areas were more active when they were required to rely primarily on sensory representations. These results were replicated in different task types and across both experiments. Similar results were also obtained by Curtis et al.  and higher statistical power due to a larger number of participants (37 vs. 23) and a generally larger number of trials.center condition, we observed stronger functional connectivity within the somatomotor network, increased functional connectivity of the somatomotor network with the cingulo-opercular network, and stronger anti-correlations with the default network. The off-center condition, which required reliance solely on retrospective sensory information, was associated with stronger integration between and within the secondary visual and dorsal attentional networks, whose functional connectivity with the posterior multimodal, cingulo-opercular, and somatomotor networks was increased.The results of the direct comparison of functional connectivity between the two conditions indicated a more prominent role of the somatomotor network when participants were biased toward the use of prospective motor coding of the response. Specifically, in the The observed pattern of differences in functional connectivity is consistent with the proposition that predictability of a motor response allows participants to prepare and maintain a motor plan, which requires integration of information within sensorimotor regions, maintenance of sensorimotor network engagement by the cingulo-opercular cognitive control network  or not (Experiment II). The presence of the fixation cue enables participants to fixate their gaze before target presentation and efficiently encode a brief stimulus, potentially improving their performance and reducing attentional engagement during the ITI. The fixation cue does, however, present a sensory event in itself, which elicits separate sensory and attentional processes that could affect estimation of target encoding processes. Importantly, the results indicate that the presence or absence of the fixation cue did not affect delay-related estimates of interest.In this study, we aimed to investigate whether slight changes in the spatial working memory task lead to the use of different strategies for encoding and maintenance of spatial information and whether we can observe their specific neural correlates. The results suggest that although the same core spatial working memory network is activated regardless of task conditions, the relative activation of individual brain regions, the dynamics of their response across trial duration, and the integration of brain activity within and between brain networks support the hypothesis that participants can encode and maintain spatial information by prospective representation of a motor response or a retrospective representation of sensory information. In the case of prospective motor coding, the motor code is generated early in the delay period and its maintenance is supported by the integration of information with and within the sensorimotor brain network. In the case of retrospective sensory coding, the maintenance of information is supported by integration with and within secondary visual and dorsal attentional networks and reactivated late in the delay period before a response is required. These results support the proposition that spatial working memory is not realized by a single representational system, but that spatial information in working memory can be encoded and maintained by multiple complementary representations, cognitive processes, and associated brain systems.https://osf.io/497ej. Whole-brain statistical maps are available in BALSA repository: https://balsa.wustl.edu/study/x2rpz.The behavioral data, EOG data and fMRI ROI activity and functional connectivity data and analysis scripts are available in OSF repository: The studies involving human participants were reviewed and approved by the Ethics Committee, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia, and the National Medical Ethics Committee, Ministry of Health, Republic of Slovenia, Ljubljana, Slovenia. The patients/participants provided their written informed consent to participate in this study.NP, MS, AS, and GR: conceptualization. NP, MS, and GR: methodology. NP, AK, AM, and GR: software. NP: formal analysis, writing—original draft, visualization, and project administration. NP, MS, AS, AK, and AM: investigation. NP, AS, AK, AM, and GR: writing—review and editing. GR: supervision and funding acquisition. All authors contributed to the article and approved the submitted version.This work was supported by the Slovenian Research Agency .GR consults for and holds equity in Neumora Therapeutics and Manifest Technologies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The human milk proteome comprises a vast number of proteins with immunomodulatory functions, but it is not clear how this relates to allergy of the mother or allergy development in the breastfed infant. This study aimed to explore the relation between the human milk proteome and allergy of both mother and child.Proteins were analyzed in milk samples from a subset of 300 mother-child dyads from the Canadian CHILD Cohort Study, selected based on maternal and child allergy phenotypes. For this selection, the definition of “allergy” included food allergy, eczema, allergic rhinitis, and asthma. Proteins were analyzed with non-targeted shotgun proteomics using filter-aided sample preparation (FASP) and nanoLC-Orbitrap-MS/MS. Protein abundances, based on label-free quantification, were compared using multiple statistical approaches, including univariate, multivariate, and network analyses.Using univariate analysis, we observed a trend that milk for infants who develop an allergy by 3 years of age contains higher abundances of immunoglobulin chains, irrespective of the allergy status of the mother. This observation suggests a difference in the milk’s immunological potential, which might be related to the development of the infant’s immune system. Furthermore, network analysis showed overall increased connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately develop an allergy. This difference in connectivity was especially noted for proteins involved in the protein translation machinery and may be due to the physiological status of the mother, which is reflected in the interconnectedness of proteins in her milk. In addition, it was shown that network analysis complements the other methods for data analysis by revealing complex associations between the milk proteome and mother-child allergy status.Together, these findings give new insights into how the human milk proteome, through differences in the abundance of individual proteins and protein-protein associations, relates to the allergy status of mother and child. In addition, these results inspire new research directions into the complex interplay of the mother-milk-infant triad and allergy. Having an allergy can strongly impact someone’s quality of life in terms of dietary, social, and psychological factors. The burden of allergic diseases for healthcare is increasing in western countries . In an aThe role of human milk in the development of allergic diseases has received considerable attention in recent years –5. BreasIt is possible that specific components in human milk with levels determined by individual-specific factors could influence the development of the immune system of the breastfed child. Proteins are a particularly important group of such human milk components with immunomodulatory potential, including immunoglobulins (Igs), cytokines, and dietary antigens.β2 in human milk were related to a higher occurrence of eczema in the infant. Österlund et al.  during lactation transferred protection for this allergen to their offspring at a level that correlated with the level of BLG-specific antibodies in the milk.In addition to these studies showing the importance of human milk proteins, some studies show the presence of dietary allergens in human milk and their possible relation with maternal and infant allergy status. It was shown, for example, that a bovine milk allergen is more abundant in milk from allergic mothers  and thatThe research to date has been mostly limited to targeted, assay-based protein analysis, with a small number of identified proteins. As a result, little is currently known about the relation between the complete human milk proteome and the allergy status of mother and child. We set out to investigate this, using human milk samples from a subset of the Canadian CHILD Cohort Study, a general population birth cohort . This sua priori. An example of a cause of such associations is that proteins have a shared location of synthesis, mechanism of transport, physical interaction, or molecular function, resulting in a correlation in their abundances. The protein connectivity  and their associations (edges or connections) expressed by a similarity measure such as correlation coefficient. The cause of protein-protein associations  can be due to different factors, and no hypothesis is set ectivity Figure 2ectivity , 24. Anaectivity . Compariectivity .This study aimed to explore the relation between the complete human milk proteome on the one hand and both maternal allergy and child allergy development on the other hand, and is the first to undertake an untargeted analysis of the human milk proteome to examine this.n = 300 mother-child dyads originating from the CHILD cohort (https://www.childstudy.ca) (This study included a subset of tudy.ca) . In the n = 75) were created . These 4 groups are later referred to as “mother-child allergy groups.” The groups were matched for lactation stage, maternal age, maternal BMI, secretor status, ethnicity, and infant sex.The selection of the 300 mother-child dyads for the current study was made based on the allergy status of the mother and the child Figure 1The definition of maternal allergy included at least one self-reported diagnosis of allergic disease, including asthma, food allergy, hay fever, or skin allergy, at the time of enrollment during pregnancy.Alternaria alternata, cat hair, dog epithelium, house dust mites [Dermatophagoides pteronyssinus and Dermatophagoides farinae], and German cockroach)) and four food allergens . According to the criteria described by Williams et al.  with one or more of the following: atopic dermatitis (1 or 3 years of age), recurrent wheezing (1 year of age), asthma (3 years of age), rhinitis (3 years of age), or food allergy (3 years of age). Atopic sensitization was determined using standardized skin prick tests, including six inhalant allergens  assay , and samples were diluted in 100 mM Tris to a concentration of 1 µg/µL protein. The diluted skimmed milk samples were prepared with filter-aided sample preparation (FASP) for protein analysis in randomized order as previously described .μL of tryptic peptide solution was loaded onto a 0.10 × 250 mm ReproSil-Pur 120 C18-AQ 1.9 μm beads analytical column (prepared in-house) at 825 bar. A gradient from 9 to 34% acetonitrile in water with 0.1% formic acid in 50 min (Thermo nLC1000) was used. Full scan FTMS spectra were obtained using a Q-Exactive HFX  in positive mode between 380 and 1400 m/z.Trypsin digested proteins were analyzed with LC-MS/MS as described before, with minor adjustments . In shorm/z and 24% normalized collision energy. MSMS scans were recorded in data-dependent mode with a threshold of 1.2 × 105 and 15 s exclusion for the selected m/z ± 10 ppm. Samples were analyzed with a technical replicate added randomly to each 7 injections.The 25 most abundant positively charged peaks  , in which also a cow milk protein  and an allergen protein database (n = 721) were added, as described before  . Proteind before .In MaxQuant, digestion specificity was set to Trypsin/P, with maximally 2 missed cleavages. A fixed propionamide modification was set for cysteines and variable modifications for acetylation of the peptide N-term, deamidation of the side chains of asparagine and glutamine, and oxidation of methionine, with a maximum of five modifications per peptide were set.Label-free quantification (LFQ) was used to obtain protein abundances. Per identified protein group, a leading protein was selected as described before  and protvia the PRIDE   was applRandom Forest  classifiFor a more complete investigation of the proteome, relationships among proteins need to be considered. Such relationships between proteins can be captured using an index of association like a correlation coefficient . Proteinn iterations = 1000), 75% of each dataset was randomly selected and subjected to the CLR algorithm. This process resulted in a matrix with a probabilistic measure ijp for each correlation between proteins rij, where i and j indicate the i-th and j-th protein in the Spearman correlation matrix. With this resampling protocol, the likelihood of each observation is obtained. The output, a probabilistic network, contains estimates of how probable the association between any two proteins is. Correlations were retained if ij >p0.99 and all other correlations were replaced with 0.With resampling  were considered for further analysis and interpretation.All rrection . SignifiTo explore comprehensively the (dis)similarity among the protein association networks, Covariance Simultaneous Component Analysis (COVSCA) was used . With thIn comparing networks with COVSCA, each network becomes a point in the component space. Thus, the method enables a representation and visualization of multiple networks in a way that is similar to PCA. Points (protein association networks of different sample groups) that are close to each other in the R-dimensional space share similar characteristics, i.e., similar correlation patterns between protein abundances. Furthermore, the loadings of the components give the relative contribution of each protein in shaping the observed network differences.K matrices are modeled as a combination of low dimensional prototypes (L<< K):COVSCA, initially developed for modeling multiple covariance matrices at the same time, can also be used for the adjacency matrices resulting from PCLRC. The klc ≥ 0 are weight coefficients, and Z of size J × lR that hold simultaneously for all kS.In this, z-scores and loadings with z > |2| were further investigated.Two rank-1 prototype matrices were used to fit the model, resulting in one set of loadings per component. This fit was chosen as the best compromise between goodness off it (74%) and the complexity of the COVSCA model . COVSCA loadings were transformed to http://cbl-gorilla.cs.technion.ac.il/) tool  (l/) tool  was usedrrection , and conα-lactalbumin, albumin, lactoferrin, β-casein, and αs1-casein, were in all analyzed samples among the 15 most abundant proteins. A complete overview of the 687 identified proteins can be found in Proteomic analysis of all samples led to a total of 1690 identified proteins before filtering on missing values. After filtering these proteins on the requirement of being identified ≥ 25 times in at least one of the four mother-child allergy groups, 687 proteins remained for further data analysis. In this filtered dataset, the number of identified proteins per sample ranged between 242 and 636 (median = 480). The major milk proteins post-hoc tests and subsequent correction for multiple testing, which resulted in 30 proteins that showed a difference between the groups with corrected p < 0.05  were found between the non-allergic group (M-C-) and the group where only the child ultimately developed an allergy (M-C+). Proteins that differed between these groups were primarily Ig chains (15 out of 17) and were mostly higher in abundance in the group where the mother was non-allergic and the child developed an allergy , including albumin from dog, horse, and cat, as well as bovine αs1-casein and BLG  allergic mother and non-allergic child, (ii) non-allergic mother and allergic child, and (iii) allergic mother and child groups. From these proteins, 95 proteins occurred in all three selections, showing a similarity in differential connectivity. Interestingly, GO overrepresentation analysis of these proteins showed a significant overrepresentation of proteins involved in translation initiation (p = 1.08 × 10-15). This overrepresentation is due to 23 ribosomal proteins and translation elongation factor EEF1A1P5.To investigate this pattern further, proteins with differential connectivity > 50 were selected for further investigation , the synthesis of glucose. This component accounts for separation between the non-allergic group and the other three groups. The second component, which drives the separation of the groups on allergy status of the child, shows a significant overrepresentation of proteins involved in the positive regulation of DNA biosynthetic processes (p = 0.0013). This overrepresentation is mainly due to 5 members of the tailless complex polypeptide 1 ring complex (TRiC or CCT). In addition, several proteins involved in translation processes show differences in correlation patterns on this component.The loadings for component 1 see Figure 8We investigated the associations of human milk proteins with maternal and child allergy. Using univariate analysis, predictive modeling, and network analysis, several relevant differences and distinctive patterns were found between groups differing in allergy status.p-values, and discuss the findings.Several proteins showed differences in relative abundance when the different mother-child allergy groups were compared. Although none were statistically significant after traditional correction for multiple testing, this does not necessarily imply they are biologically insignificant. It is widely acknowledged that correction methods for multiple hypothesis testing can be too stringent for bottom-up proteomics data , 50 becai) why do these mothers secrete these specific Igs in higher abundance in their milk, and (ii) could the development of allergy in children be related to these Igs?Most of the differences in protein abundance were found between non-allergic mothers with non-allergic children and the group where only the child developed an allergy. This result was also reflected in the accuracy of the Random Forest classification model for these two groups, which was the highest (60%) among all models. The differentially abundant proteins were mainly Ig variable domains. These results point to differences in specific Igs in milk consumed by children who ultimately develop an allergy, and these differences did not seem to be directly linked to the mother’s allergy status. This finding raises two important questions for future research: . This and other contradictions with prior studies could be related to our clinical definition of allergy. For example, in a previous study, significant differences were observed in comparing milk from mothers with house dust mite allergy and non-allergic mothers  if these would have distinct associations with milk proteins.In summary, this study set out to investigate the human milk proteome and its relations with both maternal allergy status and child allergy development. The results show trends in differential abundances of immune-related proteins between the mother-child allergy groups, suggesting possible variation in the immunological potential of human milk. However, an attempt to exploit these differences to build Random Forest classification models resulted in low predictive power. This outcome was confirmed with multivariate exploratory analysis which did not show differences in the data structure for the different groups. Interestingly, using a network approach, which enables investigation of protein-protein associations, significant differences were found among the different groups. The major finding was an overall stronger connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately developed an allergy, showing that the allergy status of either mother, child, or both is reflected in the interconnectedness of the milk proteins. Collectively, these results show that network analysis complements univariate analysis, multivariate analysis, and classification models to reveal complex relationships between maternal-child allergy phenotypes and the human milk proteome. Specifically, the network analysis points to a difference in the regulation of translation processes and protein folding in the groups where the child ultimately developed an allergy, possibly reflecting the physiological state of the mother. Further research is warranted to investigate these associations and the implicated biological pathways to understand their possible functional role in allergy development and prevention.The data presented in the study are deposited in the PRIDE repository, accession number PXD034806.The studies involving human participants were reviewed and approved by Human Research Ethics Boards at McMaster University, the Hospital for Sick Children, and the Universities of Manitoba, Alberta, and British Columbia. The patients/participants provided their written informed consent to participate in this study.KH and MA conceived the original idea and project planning. KH, PD, and MA contributed to the study design. MA, PM, TM, ES, PS, and ST organized the clinical study and actively recruited patients. PD and SB carried out laboratory work and experiments. PD and ES performed the data analysis. PD drafted the manuscript. Review and editing was done by KH, ES, and MA. All authors contributed to the article and approved the submitted version.This research was funded by the Netherlands Organization for Scientific Research (NWO-TTW) (project number 15299). The Canadian Healthy Infant Longitudinal Development study was supported by both the Canadian Institutes of Health Research (CIHR) and the Allergy, Genes and Environment (AllerGen) Network of Centres of Excellence.The authors dedicate the paper to the bright memory of Jacques J.M. Vervoort, a friend and recognized scientist, who passed away in July 2021. JV contributed substantially to the conception and design of this study. The authors thank Bassel Dawod for his help with the samples and the method section, and thank the CHILD Cohort Study (CHILD) participant families for their dedication and commitment to advancing health research. In addition, we are grateful to everyone without whom this study could not have been completed, including all members, and staff of the CHILD Cohort Study. These include research staff, administrative staff, volunteers, lab technicians, statisticians, and clinical staff at the following institutions: McMaster University, University of Manitoba, University of Alberta, University of Toronto, and University of British Columbia.MA holds a Tier 2 Canada Research Chair in the Developmental Origins of Chronic Disease at the University of Manitoba and is a Fellow in the Canadian Institutes for Advanced Research (CIFAR) Humans and the Microbiome Program. She receives research funding from the Canadian Institutes of Health Research, Research Manitoba, the Canada Foundation for Innovation, the Bill and Melinda Gates Foundation, the Manitoba Children’s Hospital Foundation, Prolacta Biosciences, Mitacs, CIFAR, the Garfield Weston Foundation, Health Data Research UK, and Canadian COVID Immunity Task Force. She regularly speaks at conferences and workshops on infant nutrition, some sponsored by Prolacta Biosciences, and has spoken at a conference sponsored by AstraZeneca. She has contributed without remuneration to online courses on breast milk and the infant microbiome produced by Microbiome Courses. She serves in a volunteer capacity for the International Society for Research on Human Milk and Lactation and as a member of the US Canada Joint Human Milk Initiative. She has consulted for DSM Nutritional Products and serves on the Malaika Vx Scientific Advisory Board.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Neuropathic pain (NP) is caused by damage or disease affecting the somatosensory nervous system. The aim of this study was to evaluate the clinical characteristics, pathophysiologies, and treatments applied in pediatric cancer patients with NP.Patients with cancer having NP between 5 and 18 years of age who were followed up in the pediatric oncology clinic of Okmeydani Training and Research Hospital between January 2015 and April 2019 were included in this study. NP was described as tingling, burning, and stinging. Patients with acute lymphoblastic leukemia and brain tumors were excluded from the study. A number of pediatric cancer patients were also recorded. Patients’ age, gender, cancer diagnosis, NP characteristics and causes, treatments, and response to those treatments were investigated retrospectively and groups of NP according to their pathophysiological mechanism were established.NP was found in 26 (16%) of 160 patients followed up for childhood cancers. The average age was 11.8±4 years. Ten of the patients (38.4%) were female, and 16 (61.5%) were male. Osteosarcoma was the most common diagnosis in 10 (38%) patients. The most common cause of NP was compression of a nerve/root/spinal cord in 9 (35%) patients and the second most common was related with limb-sparing surgery. NP was found to be associated with chemotherapy (CT) in 5 (19%) patients, mostly with vincristine. Gabapentin was administered in a total of 22 (85%) patients for treatment. Opioid administration was more common as the disease stage progressed (p<0.05). A good or partial response to treatment was achieved in 19 (73%) patients.NP can occur in childhood cancers and is related to the cancer itself, CT, surgical treatment, and disseminated disease. Although there is no standard protocol, gabapentin and, for advanced-stage patients, opioids are the most commonly used treatment options. There is no standard treatment for NP in patients with childhood cancer.We found that in the treatment of NP, the frequency of opioid use increased significantly as the stage of cancer increased independently of the type of cancer.A single gabapentin or a combination treatment can be useful for the main treatment in patients with NP.Children with cancer may experience various types of pain at the time of diagnosis, during chemotherapy (CT), and as the disease progresses. Different pain mechanisms may involve somatic, visceral, and neural tissues . NeuropaChildhood cancer patients with NP between 5 and 18 years of age followed up in the pediatric oncology clinic of the Okmeydani Training and Research Hospital between January 2015 and April 2019 were included in the study. We do not have a palliative care department or any special pain department for pediatric oncology patients, so pediatric patients with NP and cancer could only be reached through the pediatric oncology clinic to be included in the study.To evaluate the frequency of NP in our oncology clinic, the total number of pediatric cancer patients with similar characteristics as those investigated in this paper was recorded during the study. Pain in the form of tingling, burning, and stinging was evaluated as NP. Patients with acute lymphoblastic leukemia (ALL) were excluded from the study because those patients were treated in pediatric hematology clinic in our hospital. And also, CNS tumors were excluded from the study. Other exclusion criteria were prior treatment for a different cancer, having a neuromuscular disease associated with NP, and having an intellectual disability that would make it difficult to describe NP. Information about patients’ age, gender, cancer diagnosis, cancer stages, diagnostic features, laboratory investigations, NP characteristics and causes, treatments, and response to those treatments was recorded retrospectively. Five major pathophysiological groups were identified: After-amputation, after-limb-sparing surgery, associated with CT/radiotherapy (RT), nerve/root/spinal cord compression by a tumor, and disseminated disease. If NP occurred after amputation/limb-sparing surgery, it was grouped into these two categories. NP was considered to be CT related if CT had been administered within the previous 7 days. Nerve/root/spinal cord compression by a tumor is the responsible pathophysiology when such involvement is shown by the radiological methods and no other cause is possible. When there is widespread metastatic malignant neoplastic disease with NP and no other etiology can be detected, the NP cause was labeled as disseminated disease.For our statistical analysis, because the most common diagnosis was bone tumors, the diagnoses were divided into either bone tumors or non-bone tumors. The different stages were further separated into two groups: Stage-2-and-below and Stage-3-and-above. The drugs administered in the treatment of NP were determined according to the physician’s initiative and the clinical status of the patient. The response to treatment was classified into four groups: Complete response, intermediate response, poor response, and no response. The patients with a complete response were those who had a complete or almost complete disappearance of the pain with treatments. Those participants with an intermediate response experienced a significant reduction in pain; patients with a poor response had inadequate pain relief, and those in the no response group had pain that did not diminish at all. After the first drug treatment, the second or third drug treatments were given to patients in the poor response and no response groups. The response status was defined as the final status of the patient after all treatments. Informed consent was obtained from the patients and their relatives before treatment. The Okmeydani Training and Research Hospital Ethics Committee of our institution approved the study (2019/1322).Descriptive statistical analyses were performed to determine the demographic data, clinical data, and treatment of the patients. A Chi-square test was used for categorical variables. All statistical tests were performed using the Statistical Package for the Social Sciences, Chicago, USA, version 21.0.In total, 160 patients were observed in the pediatric oncology clinic during the study period due to non-ALL and non-CNS cancers; 26 of them (16%) had NP. Ten (38.4%) of the patients were female, and 16 (61.5%) were male. The average age was 11.8±4 years; the median age was 12.5, while the youngest patient was 5 and the oldest was 18. Osteosarcoma was the most common diagnosis in 10 (38%) patients, followed by Ewing’s sarcoma in 5 (19%) patients. Seven patients (27%) were in Stage 2, 9 (35%) were in Stage 3, 9 (35%) were in Stage 4, and 1 (3%) was in Stage 2 but not responding to CT. The most common cause of NP in 10 (38%) patients was compression of a nerve/root/spinal cord by a tumor. The pathophysiologies and the primary diagnoses are presented in Primary tumor localization was most commonly in the distal femur in osteosarcoma patients and in the iliac bone in Ewing’s sarcoma patients. All patients reported tingling, burning, and stinging pain. Twenty (77%) patients had hyperalgesia; 9 (35%) had allodynia, and all patients with allodynia also experienced hyperalgesia. All patients received CT. In five patients, NP was considered to be associated with CT, most commonly vincristine followed by cisplatin. Only one patient had received triple CT with brentuximab, vincristine, and cisplatin. Vincristine was withdrawn from treatment in one patient who underwent surgery for pleuropulmonary blastoma due to neuropathy, but the other patients completed their CT treatment. One patient with non-Hodgkin’s lymphoma had a diagnosis of ataxia telangiectasia confirmed by genetic analysis. The patient with Stage 2 Hodgkin’s lymphoma that did not respond to CT had undergone autologous stem cell transplantation followed by brentuximab vedotin. That patient had reported no symptoms of NP or neuropathy before treatment with brentuximab vedotin monotherapy. NP was treated with a single drug in 17 patients; 15 (58%) received gabapentin, one received fentanyl, and one received a nonsteroidal anti-inflammatory drug (NSAID) as the single agent. Gabapentin was administered in single or combination treatment in 22 (85%) patients. In nine patients, NSAIDs, gabapentin, fentanyl, and oxycodone combinations were used. NSAIDs, gabapentin, and fentanyl were combined in the treatment of a patient with Ewing’s sarcoma of the iliac bone. The pain of an operated osteosarcoma patient with phantom pain due to amputation decreased after prosthesis application. Only one patient with a malignant mesenchymal tumor had undergone physical therapy in addition to medical treatment with gabapentin. A complete response to treatment was observed in 7 (27%) patients, while 12 (46%) had an intermediate response, 2 (8%) experienced a poor response, and 5 (19%) did not respond. Nineteen (73%) patients had complete and intermediate responses, while 7 (27%) had poor responses or did not respond to treatment. Unresponsiveness was observed in two children with osteosarcomas, two children with Ewing’s sarcomas, and one child with a pancreas neuroendocrine tumor. Six patients did not survive: Three with osteosarcomas, one with Ewing’s sarcoma, one with operative neuroblastoma, and one with a pancreas neuroendocrine tumor.There was no statistically significant relationship between the stage of the disease and the presence or absence of hyperalgesia (p>0.05), but there was a statistically significant relationship between the disease stage and opioid administration status (p<0.05) . AccordiGender, age, diagnosis, disease stage, primary tumor site, cause of NP, treatment of neuropathy, response to neuropathy treatment, and final status of the all patients are listed in In our study, we found that the incidence of NP in non-CNS childhood cancers in our pediatric oncology clinic was 16% excluding leukemia. There are a few studies about NP frequency in the literature; in one of them, patients admitted to the pediatric oncology pain service for NP were evaluated, and the frequency of NP was found to be 17% . DifficuIn our study, the most common type of cancer was osteosarcoma in 10 patients; 70% of these patients experienced operation-related pain. Approximately half of the patients underwent limb-sparing surgery, and the other half had amputation. The pathophysiological cause of NP in the remaining cancer patients was determined as CT/RT related, due to tumor compression of a nerve/root/spinal cord, or the result of disseminated disease. The priority in surgical treatment is, if possible, the removal of the tumor by limb-sparing surgery and reconstruction with an endoprosthesis or allograft. In cases where a limb-sparing procedure is not feasible, an amputation is recommended.In the one and only prospective study evaluating NP after surgical treatment in pediatric osteosarcoma, it was observed that 81% of patients had NP . In factAmong the chemotherapeutic agents, as many as 50–90% of patients treated with platinum compounds, such as cisplatin and carboplatin, develop peripheral neuropathy, whereas with vinca alkaloids, the rate is 50% . In a reIn the treatment of pain in children and adolescents, the first step is NSAIDs ; when itThe key limitation of our study was its retrospective design. Because of its retrospective character, the pain level could not be evaluated, the duration of pain was not clear, and the treatment doses could not be included in the study. We also may have missed a few children harboring NP during cancer treatment because the study design was not prospective. However, in our study, we evaluated the clinical characteristics, treatment types, and treatment responses of children with cancer and also NP with different pathophysiologies followed by a single center.While 20–40% of adults experience NP during cancer [


Prostate cancer (PCa) is today the second most common cancer in the world, with almost 400,000 deaths annually. Multiple factors are involved in the etiology of PCa, such as older age, genetic mutations, ethnicity, diet, or inflammation. Modern treatment of PCa involves radical surgical treatment or radiation therapy in the stages when the tumor is limited to the prostate. When metastases develop, the standard procedure is androgen deprivation therapy, which aims to reduce the level of circulating testosterone, which is achieved by surgical or medical castration. However, when the level of testosterone decreases to the castration level, the tumor cells adapt to the new conditions through different mechanisms, which enable their unhindered growth and survival, despite the therapy. New knowledge about the biology of the so-called of castration-resistant PCa and the way it adapts to therapy will enable the development of new drugs, whose goal is to prolong the survival of patients with this stage of the disease, which will be discussed in this review. Homo sapiens, which happened relatively recently with the development of animal husbandry—animal fat, especially saturated, can contribute to PCa progression, while unsaturated fatty acids (FA) abundant in fish and vegetable oils reduce PCa risk .,4,5.3,4,The prostate secretes numerous non-peptide  and peptide substances  ,7,8,9. TAccording to 2020 GLOBOCAN data, PCa is the second most common cancer among men and the fifth leading cause of cancer death, with approximately 1.4 million new cases and approximately 375,000 deaths worldwide . The incPCa is diagnosed in only 2% of cases in people under the age of 50, and over 60% of patients are diagnosed after the age of 65 . In 2018BRCA1 and BRCA2. African Americans in the USA have the highest incidence rate globally, which is explained by African ancestry and multiple environmental factors, such as hypovitaminosis D. About 15% of PCas are thought to be hereditary. Thus, the risk of developing PCa is 2× higher if the father had PCa, 3× if the brother had PCa, and if both father and brother had PCa, as much as 5 times ..180].Finally, abiraterone is an androgen biosynthesis inhibitor in testicular, adrenal, and prostatic tumor tissue targeting CYP17. It is also an AR antagonist and 3β-hydroxysteroid dehydrogenase inhibitor with affinity for CYP11B1 and a panel of hepatic CYP enzymes. A newer drug, galeterone, also blocks CYP17, AR, and the transcriptional activity of this receptor in the nucleus of tumor cells .Other mechanisms of therapeutic targeting of the AR pathway involve pharmacological antagonism at the receptor level and inhibition of the conversion of testosterone into a more active metabolite—DHEA—which is achieved by blocking the enzyme 5α-reductase. Examples of AR antagonists include: flutamide, bicalutamide, nilutamide, apalutamide and enzalutamide .These antiandrogens bind to the ligand binding site on the AR and thus prevent androgen binding. Unlike bicalutamide, apalutamide is an antiandrogen with a high affinity for the AR that does not have agonistic activity ; it also blocks the binding of AR to DNA in the nucleus of PCa cells. Darolutamide has an advantage over enzalutamide and apalutamide, as it blocks both overexpressed and mutated AR, which is the main mechanism of resistance to the other two mentioned antagonists. Additionally, darolutamide blocks the transcriptional activity of AR with point mutations F877L, H875Y/T878A, F877L/T878A, and T878G. The clinical efficacy of AR antagonists is lower when they are used as monotherapy, since AR blockade leads to the termination of the negative feedback loop and increased secretion of LH and thus of testosterone. Better results in the treatment of metastatic PCa are achieved if AR antagonists are combined with GnRH analogues; then AR antagonists block the effects of adrenal androgens that GnRH analogues do not. A newer approach in antagonizing the AR is the blockade of the AF-1 region (activation function-1) on the N-terminal part of the AR and this is the mechanism of action of the new substance, EPI-506, which is the precursor of the active molecule EPI-002; said antagonist is in phase I/II clinical trials for patients with mCRPCa resistant to abiraterone and/or enzalutamide. Spironolactone is also a weak antagonist of AR and testosterone biosynthesis, and cyproterone acetate, a progestin, can block AR to some extent. On the other hand, finasteride and dutasteride, as 5α-reductase inhibitors, prevent testosterone from converting into DHEA, especially in the male external genitalia. Both drugs are used in the treatment of benign prostatic hypertrophy.It is estimated that 20–40% of PCa patients have a recurrence after initial radiation therapy or surgical removal of the prostate. Then, drugs that suppress endogenous androgens  are introduced into the treatment. However, 12–18 months after initiation of ADT, CRPCa develops with disease progression. AR gene amplification has been identified in 30–50% of CRPCa cases and is associated with poor prognosis and shorter overall survival, as well as shorter progression-free survival .One of the important causes of resistance to antiandrogens in PCa therapy is changes at the gene level. Muller et al. (2012) showed ten years ago that in some tumor tissues there is a co-deletion of genes that suppress tumor development and they are located in the same part of the chromosome . Such isPoint mutations of the AR gene;Amplification of AR and CYP17;Changes in androgen biosynthesis;Changes in cofactors for AR;Creation of different variants of AR.Overall, antiandrogen therapy suppresses most PCas for a certain period of time, but resistance to ADT is virtually inevitable. Nearly all cancers will progress to CRPCA if given ADT for an adequate period of time. The resistance mechanisms leading to CRPCA can be divided into five groups:These mutations are rare in primary hormone-dependent tumours but occur more frequently in CRPCa (>10%), especially in cases where the tumor has progressed despite systemic hormone therapy and the use of new antiandrogens. Not only that, but AR gene mutation is among the nine most significant gene mutations in CRPCa . The resThis resistance mechanism often occurs with ADT and plays an important role in the loss of efficacy of the new antiandrogens, enzalutamide and abiraterone. It has been identified in as many as 80% of CRPCa cases . At the Tumor cells can escape inhibition of androgen synthesis by goserelin or abiraterone by increasing, intratumorally, androgen synthesis and/or AR, but also via glucocorticoid receptors and glucocorticoids . EvadingThe EGF/IGF signaling pathway that is mediated by phosphatidylinositol 3-kinase (PI3K) and protein kinase B (Akt/PKB) and depends on the level of phosphatidylinositol 3,4,5-triphosphate (PIP3) and PTEN in the cell;The Ras signaling pathway (Ras family of proto-oncogenes) that occurs via Cdc42-linked kinase (Ack), Ras/Raf mitogen-activated protein kinase/ERK kinase (MEK), and the proto-oncogene tyrosine protein kinase Src;IL6 cytokine signaling pathway that activates AR through Janus kinase signal transducer and activator of transcription (JAK1), signal transducer and activator of transcription 3 (STAT3), and intermediate histone acetyltransferasep300.In conditions of AR blockade due to ADT, rescue pathways are activated in the form of at least three alternative signaling pathways that involve growth factors and stimulate AR signaling pathways independently of androgens, i.e., steroids :The EGF/In a tumor consisting of several million cells, there are already those that have activated drug resistance mechanisms and will contribute to the development of CRPCA. Induced resistance is also possible. However, tumor size does not necessarily increase the likelihood of developing CRPCA. There are many other factors . Shore et al. (2021) emphasized predictive factors for progression to CRPCA: Gleason score, extent of metastatic spread, hereditary genetic factors/mutations, and hormonal kinetics . For exaSignal transduction of all nuclear receptors, including AR, begins with cofactor recruitment. Previously, the ligands bound to the receptors. They subsequently move into the nucleus and form dimers with a conformational change into an active form that can interact with promoter regions. The dimer–cofactor complex (coactivators or corepressors) activates or inhibits transcription. The ligand nature determines the receptor conformation and cofactor affinity ,192.Since 1995, when the first cofactor, SRC-1, was isolated, their number has increased to over 200 . They caLi et al. (2002) showed that changes in the expression of AR cofactors could play a vital role in the development of prostate tumors. They confirmed by in situ hybridization that in PCa epithelial samples, there is increased expression of Ran/ARA24 and PIAS1 and slightly less of SRC1, TMF1/ARA160, TRAP220, ARA54, and ELE1/ARA70 . The autFujita et al. (2019) showed that the expression of proteins from the SRC family (steroid receptor coactivator), SRC1, -2, and -3, is correlated with the aggressiveness of PCa . In miceAnother AR coactivator, CBP/p300, also has an oncogenic effect. It increases during androgen deprivation, and blocking its bromodomain reduces tumor growth . SimilarWild-type full-length AR (AR-FL) consists of an N-terminal domain, a DNA-binding domain, and a ligand-binding domain , encoded by exon 1, exons 2–3, and exons 4–8, respectively. Along with AR-FL, in CRPCA, splice variants are also particularly prevalent: AR-V1, AR-V7, and AR-567. Splice variants have a low abundant LBD and can be constitutively active in androgen-responsive genes even without ligands. At the same time, AR-FL interacts with both coactivators and corepressors, while AR-V7 is mainly linked to corepressors. This is partly due to isoform-specific variations in H3K27 acetylation . The role of the HOXB13 gene and its product, the transcription factor, is vital for AR-V7 signaling as well.CRPCA resistance to enzalutamide results from the absence of the target , whereas abiraterone increases the expression of ARf1, AR-V7, and AR-567 ,198. AR-From Charles Huggins and androgen deprivation in the treatment of mPCa  to the nUntil just a few years ago, the mCSPCa treatment was exclusively via androgen deprivation with either luteinizing hormone-releasing hormone (LHRH) analogues, LHRH antagonists, or subcapsular orchiectomy. Attempts to add peripheral anti-androgens of the first generation did not lead to a prolongation of patient survival, so their administration was not recommended by experts . Today, p < 0.001) [The first study to add a specific therapy to ADT was the CHAARTED study, which compared docetaxel with placebo in mCSPCa patients. Patients were stratified into a group with “high volume” disease, which is defined by the presence of visceral metastases and/or at least four bone metastases, at least one of which is in the peduncle of the skeleton; and another group that does not have these characteristics called “low volume”. Although the study demonstrated longer survival in the intent-to-treat (ITT) population, a sub analysis found that only those patients with high-volume disease benefited  . Given tp < 0.001) and rPFS . Grade 3 side effects of hypertension and hypokalemia were more common in the abiraterone group [LATITUDE is a study that examined the addition of abiraterone to ADT in patients with initially metastatic castration-sensitive “high-risk” PCa, defined by the presence of at least two of three features: visceral metastases, at least three bony metastases, and a Gleason score ≥8. In this study, 1199 patients were randomized to either abiraterone and prednisolone or placebo and prednisolone. All patients were on ADT. Co-primary endpoints were overall survival and radiological time to disease progression. Abiraterone prolonged OS compared to placebo . The most common side effect of apalutamide was rash [p < 0.0001) despite crossover that was allowed in the study [Apalutamide is a newer generation antiandrogen. In the study, TITAN was compared with placebo in patients with mCSPCa. The study included all patients regardless of volume or risk of disease and all were on ADT. Primary endpoints were rPFS and OS. In the primary analysis, after a median follow-up of 22.7 months, the proportion of patients who were free of radiological progression in the apalutamide group at two years was 68.2% versus 47.5% in the placebo group  [Similar to apalutamide, enzalutamide has also demonstrated efficacy in mCSPCa. The ARCHES study compared enzalutamide with placebo in addition to standard ADT. Patients were stratified by disease volume and prior docetaxel use. In all subgroups, enzalutamide prolonged the time to radiological disease progression. Adverse effects of Grade 3 and greater were equally common in both groups . In an u< 0.001) . The ENZ< 0.001) .p < 0.0001) and OS . The addition of abiraterone to ADT and docetaxel did not increase the rates of neutropenia, febrile neutropenia, fatigue, or neuropathy. Triple therapy achieved the greatest benefit in high-volume disease according to CHAARTED criteria [The most recent treatment concept for mCSPCa is the so-called triple therapy, which includes simultaneous administration of ADT, antiandrogens, and docetaxel chemotherapy. The PEACE-1 study is a 2 × 2 factorial design study in which a control group of patients received standard of care (SOC) ADT plus docetaxel, one study group received SOC plus radiotherapy, one group received SOC plus abiraterone, and the last group received SOC plus abiraterone and radiotherapy. A total of 1173 patients were randomized in the study. Patients receiving abiraterone had longer rPFS . In addition, all key secondary objectives were achieved in this study: time to PSA progression, radiological time to disease progression (rPFS), as well as PSA response rate. Fluid retention, hypertension, and hypokalemia were the most common side effects in the AA group [p < 0.001). Similar to AA, all secondary objectives were met in the study with enzalutamide. The most common side effects in the enzalutamide group were hot flashes, fatigue, and diarrhea, while 0.5% of patients had seizures [As already mentioned, for a long time ADT was the only option that prolonged the survival of mCRPCa. The TAX-327 study examined three chemotherapy options in mCRPCa, three-weekly docetaxel, weekly docetaxel, and mitoxantrone. Symptomatic patients with mCRPCa, as well as those who had visceral metastases, were included in the study. The primary target was OS. Both docetaxel groups had longer OS compared to mitoxantrone. Since 2004, three-week docetaxel has become the standard treatment for symptomatic patients with mCRPCa . A littlAA group . Enzalutseizures .p < 0.001), as was median OS  [p < 0.001) and longer OS at the time of publication. In the enzalutamide group, 72% of patients were alive, while in the placebo group, that percentage was 63%  [p < 0.0001) [A large number of patients enter the mCRPCa stage of the disease due to a jump in PSA or the appearance of new asymptomatic metastases. Considering this fact, studies were developed for mCRPCa in asymptomatic or minimally symptomatic patients who had not previously received docetaxel. Study COU-AA-302 compared AA with placebo in combination with prednisolone. The study enrolled 1088 patients and the co-primary endpoints were rPFS and OS. Median rPFS was longer in the AA group  . In a st< 0.001) . In addi 0.0001) . The saf 0.0001) ,216.p < 0.001). Median OS was longer in the cabazitaxel group . The most common side effect of Gr3 cabazitaxel was neutropenia in 44.7% of patients.Cabazitaxel is a taxane cytostatic. In the TROPIC study, it demonstrated longer PFS and OS compared to mitoxantrone when discontinued after progression to docetaxel therapy . After tp < 0.001) and overall survival . Grade 3 side effects were more frequent in the 177Lu-PSMA617 group, but quality of life was preserved [Radiopharmaceuticals are an interesting field of mCRPCa treatment. The first registered radiopharmaceutical for the treatment of this disease was the alpha emitter Radium-223, which demonstrated longer OS compared to placebo in docetaxel-naïve patients with mCRPCa. This type of treatment did not show significant side effects but was reserved only for patients with bone metastases . The VISBRCA1, BRCA2, and ATM mutations, while cohort B included patients with 12 other prespecified genes. Cohort A included 245 patients, while cohort B included 142. Olaparib prolonged PFS in cohort A . In addition, benefit was shown in objective response (ORR) and time to PSA progression. Additionally, rPFS was prolonged with olaparib in the entire study population (cohorts A and B). The most common side effects of olaparib were anemia and nausea. Statistical significance for overall survival has not yet been proven in the aforementioned analysis [Comprehensive genomic profiling (CGP) and personalized therapy of malignant diseases is the focus of interest of the oncology public. ESMO recommends CGP in the treatment of mCRPCa to select the most adequate therapy . Severalanalysis . Howeveranalysis . In the analysis . We are Immunotherapy with checkpoint inhibitors (ICI) plays a significant role in the treatment of various urological tumors ,229. In The definition of castration resistance in addition to radiological progression includes an increase in PSA with the patient’s castrate testosterone level. Sometimes PSA progression occurs without visible metastases by conventional imaging methods including skeletal scintigraphy and CT scans. What is also the fact that in this situation, patients with a shorter PSA doubling have a shorter time to the appearance of metastases and a worse prognosis . In 2015Autophagy is a survival mechanism that cancer cells use to deal with metabolic stress caused by various treatments, such as castration therapy. Additionally, autophagy has been shown to promote castration resistance. Evidence suggests that the expression of CAMKK2, AMPK, and ULK1 in males with PCa is related to the disease’s prognosis and progression. When AMPK-ULK1 signaling is inhibited, autophagy, cell proliferation, and colony formation are also inhibited in Lymph Node Carcinoma of the Prostate (LNCaP) cells. These findings add to the growing evidence that the CAMKK2-AMPK-ULK1 signaling cascade promotes autophagy and, thus, PCa and castration resistance .Despite their distinct action methods, abiraterone and enzalutamide are currently used in treating CRPCa. Enzalutamide is a drug that exerts multiple effects on androgen signaling, including: (i) the inhibition of testosterone binding to AR, (ii) the suppression of AR nuclear translocation, and (iii) the inhibition of AR binding to DNA. It has been demonstrated that the administration of enzalutamide induces an autophagy cascade in the C4-2B subline of LNCaP cells, which is mediated by the activation of AMPK and the inhibition of mTOR. This subpopulation of cells can replicate the behavior of CRPCa in humans by growing in castrated hosts. Moreover, it has been demonstrated that inhibiting AMPK in cells exposed to enzalutamide inhibits autophagy and promotes cell death. These results indicate that autophagy is a crucial survival strategy in CRPC . HoweverThe same evidence has been presented in the study of apalutamide, another AR antagonist used in CRPCa. Apalutamide treatment of LNCaP cells induces autophagy, which has been shown to have a strong anti-tumor effect when combined with autophagy inhibitors such as 3-methyladenine or siRNAs . LNCaP cStandard treatment for men with metastatic PCa or CRPCa includes the microtubule-stabilizing drug docetaxel. A number of studies have demonstrated that autophagic activity during taxane-based therapy varies considerably. While some research suggests that taxane therapy may stimulate autophagy, others have found the opposite to be true ,247. HowClinical responses after receiving prostate-specific membrane antigen (PSMA)-targeted radioligand treatment (RLT) with 177Lu or 225Ac radionuclides have been seen in between 57 and 76% of PCa patients ,250. HowADT remains the mainstay of primary PCa pharmacotherapy, but not as a monotherapy in most metastatic patients. Remission after ADT usually lasts 1–4 years, although in some cases it is longer (10 years). New strategies in the treatment of this malignancy include the development of inhibitors of androgen signals, the use of a combination of antiandrogens as a gold standard, as well as intermittent regimens of these drugs. Survival is prolonged, but still the cancer returns; that is, there is an exacerbation. It is a fact that even in CRPCa, cancer cells are dependent on androgens, but the mechanism of resistance to antiandrogens often remains unknown ,253,254.Not all targets listed in Another novel approach in PCa treatment could be modulation of autophagy. There have been a number of attempts to restore sensitivity to docetaxel or ADT by inhibiting autophagy. In preclinical models, the results have been encouraging because blocking autophagy has been shown to increase cell death in response to anti-cancer treatment. Currently, the focus of research is on conducting clinical trials to verify the findings of preclinical reports in patients with refractory malignancies . Small iRecently, the efficacy of chloroquine in combination with metal-based chemotherapeutic drugs such as palladium has been investigated . The palOther inhibitors, such as metformin or fenofibrate, have also been studied. Metformin is an oral biguanide frequently used to treat type 2 diabetes, well known by mTOR inhibition. While it is expected that this should increase autophagy, metformin actually inhibits autophagy by blocking Beclin-1 . A recenUnfortunately, the clinical use of these drugs could be challenging. For example, a high dose of pantoprazole, a drug that has been considered as a possible chemotherapy adjuvant, was shown to be beneficial in blocking autophagy and preventing taxanes resistance in a variety of solid tumors . However


Staphylococcus aureus bacteremia (SAB), but routine clinical antimicrobial susceptibility testing takes an additional 24 h after species identification. Recent studies elucidated matrix-assisted laser desorption/ionization time-of-flight mass spectra to discriminate methicillin-resistant strains (MRSA) or even incorporated with machine learning (ML) techniques. However, no universally applicable mass peaks were revealed, which means that the discrimination model might need to be established or calibrated by local strains’ data. Here, a clinically feasible workflow was provided. We collected mass spectra from SAB patients over an 8-month duration and preprocessed by binning with reference peaks. Machine learning models were trained and tested by samples independently of the first six months and the following two months, respectively. The ML models were optimized by genetic algorithm (GA). The accuracy, sensitivity, specificity, and AUC of the independent testing of the best model, i.e., SVM, under the optimal parameters were 87%, 75%, 95%, and 87%, respectively. In summary, almost all resistant results were truly resistant, implying that physicians might escalate antibiotics for MRSA 24 h earlier. This report presents an attainable method for clinical laboratories to build an MRSA model and boost the performance using their local data.Early administration of proper antibiotics is considered to improve the clinical outcomes of  Staphylococcus aureus accounts for 20% to 30% of culture-positive infections and 20% of bloodstream infections among intensive care unit (ICU) patients 43], RF , and SVMfeature_importances” in the DT to calculate the importance for each feature. Thus, before calculating feature importance, we must build the DT for the training samples. For a decision tree, scikit-learn calculates a node importance, denoted as jNI for node j, using Gini impurity , as calculated byinormFI is the normalized Feature Importance of feature i.The importance for each feature is calculated by .(3)FIi=n is the number of elements in the FPR data set, itpr denotes the i-th data point of TPR, and ifpr is the i-th data point of FPR.ML model performance was assessed by accuracy, sensitivity, specificity, and Area Under a receiver operating characteristic (ROC) Curve (AUC). The horizontal axis of the ROC curve is the false positive rate (FPR), equal to 1—specificity, and the vertical axis is the true positive rate (TPR). A trapezoid is formed between two false positive rate points, and thus, AUC is calculated by the sum of the area of all trapezoids. Definitions are shown below:mec (SCCmec)-typed MRSA isolates. All these strains, generously provided by Infectious Diseases Laboratory, Department of Medical Research, Chi Mei Medical Center, had been typed by multiplex PCR in other study [To further clarify the bias of the ML models, classification accuracy was assessed by another 110 Staphylococcal Cassette Chromosome er study  and storA total of 26,159 peaks were obtained from the training sample set, and 508 reference peaks were extracted by the modified binning method. A data matrix with 366 (147 MRSA and 219 MSSA isolates) × 508 (features) was used for model construction, and another data matrix with 182 (72 MRSA and 110 MSSA) × 508 (features) was applied for independent testing. Because the 508 reference peaks were generated from the training samples, some peaks in the testing samples were inevitably lost because they were not fit for the bins of reference peaks. For example, a peak at m/z 2166.273 was observed in an independent sample, but the two closest reference peaks ranged from 2149.044 to 2157.791 and from 2166.364 to 2172.865. To address the influence of peak loss, we first evaluated whether 366 samples were enough to construct reference peaks by comparing feature numbers generated from different sample sizes. More than 50% of reference features were generated by one-tenth of the total samples , and theThis study investigated the classification performance of the four ML models for four different data sets as described below under three feature selection strategies.feature_importances_, in the decision tree algorithm of the scikit-learn package of Python to calculate the Feature Importance of each feature. We repeated the experiment 100 times, and conducted the following procedures for each experiment:From 366 samples, 80% of the samples were randomly selected as training samples, and the remaining 20% were used as testing samples.A decision tree model was constructed based on the training samples as mentioned in (1), and Feature Importance was calculated for each feature.There were three strategies to select features for each sample in the training and testing samples mentioned in (1).(3-1) Among the 508 features, only those whose Feature Importance were greater than 0 were retained, and remaining features were deleted.(3-2) Only the top 15 features in terms of Feature Importance were kept, and the remaining features were deleted.(3-3) All 508 features were retained.The four ML models were built based on the training samples with the features selected in the above (3-1) to (3-3). The classification performances of the four ML models for items (3-1) to (3-3) were evaluated.There was a total of 366 samples in each data set, and each sample had 508 features. This study used one of the functions, i.e., C = 100, and γ = 3.4425 × 10−5. The highest polynomial order of PR model is 1. DT and RF models use the default parameters. The words “important feature” as shown in Condition 1 and 2 of The experimental results for the S/N data set are shown in According to the training samples as mentioned in item (1), there were about 31 features with an average Feature Importance > 0. As shown in The classification performances of the testing samples of the four ML models for different data sets under different feature selection strategies are shown in The SVM model had the highest sensitivity and specificity when using all 508 features B,C. In tTo save time, this study used GA to find acceptable and satisfactory rather than optimal parameters of SVM, DT, and RF models.degree of the PR model. As shown in In the PR model, only one parameter needed adjustment, i.e., the C and γ parameters, and the kernel function was set as ‘RBF’. The chromosome design and the definition of fitness function of a chromosome of GA are shown in the text of the Supplement and in C = 719.66, γ = 0.0001, and the number of features was 13 .GA was used to search the optimal parameters of SVM, including feaN (the number of features in the samples).GA was used again to search for the optimal DT parameters. This study used the DT model of the scikit-learn package of Python . We applied GA to investigate the following parameters: criterion (Cr), splitter (Sp), max_depth (MD), min_samples_split (MSS), min_samples_leaf (MSL), ccp_alpha (CA), and feaN = 7 . The maximal and average fitness values during evolution are shown in The chromosome design of GA for searching best parameters of DT is shown in feaN = 5 .Because RF is composed of multiple DTs, many parameters of RF and DT are identical. As with the DT parameters described above, this study deleted the first two parameters (Cr and Sp) and added two RF parameters, i.e., bootstrap (BS) and n_estimators. The BS parameter is employed to decide whether BS samples are used to build samples. If it is false, the whole dataset is used to build each tree. n_estimators (NE) indicates the number of trees in the forest. In this study, GA is still used to search for the optimal parameters of RF. Here, the chromosome design of GA is like The investigation demonstrated that the ML models trained by the optimal parameters and using the selected features could provide better performance, especially for the SVM model in which the AUC value increased from 0.5910 to 0.8664 (accuracy increased from 0.5879 to 0.8736). In the independent testing, the SVM model performed best, with accuracy, sensitivity, specificity, and AUC of 0.8736, 0.7500, 0.9545, and 0.8664, respectively. The assessment of accuracy, sensitivity, and specificity and the evaluation of AUC were performed at different times. The ROC curves of the independent testing for the four ML models with and without optimal parameter settings are shown in A total of 110 MRSA isolates carrying four types of SCCmec were investigated to clarify bias against different stains. By using the best models trained by clinical samples, the accuracy varied in different SCCmec types. The models were able to recognize most type III and more than half of type IV and V isolates, but nearly none for type II  explored bin size ranging from 1 to 15 m/z, and found that the best classification performance was obtained when using 10 m/z . HoweverThe types of data value to represent feature intensities may influence classification performance, and S/N seems to be the best measure in comparison with IN, RI, TIC in this study . GeneralfeaN = 13. The possible reason for the inconsistency between the two is that the parameters of SVM, i.e., C and γ, are set differently, which will lead to different optimal number of features. The SVM parameters of C = 100 and γ = 3.4425 × 10−5, and the optimal parameters found after GA evolution were C = 719.66 and γ = 0.0001.First, SVM seeks to find a linear or non-linear boundary (the linear boundary is a hyperplane) to distinguish different classes of data . Only bySecondly, PR is a special case of multiple linear regression . In the Third, RF is composed of several decision trees. When the number of considered features increases, the decision tree is larger, and the number of rules is greater. Subsequently, the classification efficiency of the training samples is higher, but the efficiency of the testing samples is relatively poor. This is the phenomenon of overfitting, that represents an over-adjustment of parameters to suit the training samples and may therefore fail to fit additional data or predict future observations reliably . TherefoThe use of GA requires a prior determination of the number of chromosomes (population size) and the number of genes in each chromosome. The number of genes depends on the encoding method of the parameters, which are solutions of a problem, and can be determined according to the needs of the problem. For an example, please refer to Supplemental The classification performances of the training samples of the SVM and PR models were like the performances of the testing samples . HoweverS. aureus [S. aureus bacteria were resistant. Feature importance scores calculated by RF, whereas we calculated by DT, to find the appropriate number of features to classify the three antibiotic resistances separately. The features were ranked by their important scores, and then added in the model sequentially until the accuracy reached a plateau. They selected 36, 38, and 37 features for oxacillin, clindamycin, and erythromycin models, respectively. Instead, we applied the GA to find the optimal number of features under a certain combination of parameters. As discussed earlier, SVM has different optimal number of features for different parameter combinations. Thus, the number of features found Chung et al.’s study may not fit optimal parameter combination. In addition, Chung et al. used the grid search to find the optimal parameters for ML models [Chung et al. developed a web tool for the rapid identification of oxacillin-, clindamycin-, and erythromycin-resistant . aureus . They alL models . When thmec-typed MRSA pointed out it is important to establish ML models by regional samples to avoid differences between training and testing samples, and post-implementation evaluation and recalibration would be needed because the prevalence of genotypes might change from time to time.Our results demonstrated that parameter optimization has a very significant impact on model performance. These ML methods offer their best performance after parameter optimization in different applications. Because of different applications, the data patterns are different. The parameters of the ML models must be adjusted to suit the data patterns for a specific application. The classification performances of SVM, RF, and PR models improved significantly when optimal parameter settings were used . BesidesAlthough the model results were not identical to those of AST, we propose the model is still worth to incorporate into clinical workflow. Once a model is established, the only additional task for a laboratory staff is taking few minutes to operate a computer to analyze sample data. In comparison, most rapid assays, no matter genotypic or phenotypic methods ,67, may To our knowledge, this study is the first example of the use of a modified binning method to extract features. Four ML models were tested to classify MRSA and MSSA, and parameters were searched by GA. The classification performance was markedly improved after parameter optimization. The classification results of independent testing showed that SVM was the best model, with accuracy, sensitivity, and specificity of 87%, 75%, and 95%, respectively, and an AUC of ROC curve of 0.8662. In addition to acceptable model performance, independent testing proved that the process and ML model were applicable to new samples as in real-life situations in clinical laboratories. Although thorough validation is required before clinical implementation, these results may facilitate studies of whether clinical outcomes may be enhanced by the early discrimination of MRSA.