Schizosaccharomyces pombe. During the meiotic program, genes encoding copper transporters exhibit distinct temporal expression profiles. In the case of the major facilitator copper transporter 1 (Mfc1), its maximal expression is induced during middle-phase meiosis and requires the presence of the Zn6Cys2 binuclear cluster-type transcription factor Mca1. In this study, we further characterize the mechanism by which Mca1 affects the copper-starvation-induced expression of mfc1+. Using a chromatin immunoprecipitation (ChIP) approach, results showed that a functional Mca1-TAP occupies the mfc1+ promoter irrespective of whether this gene is transcriptionally active. Under conditions of copper starvation, results showed that the presence of Mca1 promotes RNA polymerase II (Pol II) occupancy along the mfc1+ transcribed region. In contrast, Pol II did not significantly occupy the mfc1+ locus in meiotic cells that were incubated in the presence of copper. Further analysis by ChIP assays revealed that binding of Pol II to chromatin at the chromosomal locus of mfc1+ is exclusively detected during meiosis and absent in cells proliferating in mitosis. Protein function analysis of a series of internal mutants compared to the full-length Mca1 identified a minimal form of Mca1 consisting of its DNA-binding domain (residues 1 to 150) fused to the amino acids 299 to 600. This shorter form is sufficient to enhance Pol II occupancy at the mfc1+ locus under low copper conditions. Taken together, these results revealed novel characteristics of Mca1 and identified an internal region of Mca1 that is required to promote Pol II-dependent mfc1+ transcription during meiosis.When reproduction in fungi takes place by sexual means, meiosis enables the formation of haploid spores from diploid precursor cells. Copper is required for completion of meiosis in  Schizosaccharomyces pombe, a diploid precursor cell is formed by conjugation of two haploid cells of opposite mating types. Following conjugation, the two haploid nuclei fuse and that subsequently induces replication of chromosomal DNA, generating pairs of homologous chromosomes. After meiotic recombination between homologous chromosomes that increases genetic diversity, two successive meiotic divisions occur in which homologous chromosomes (meiosis I) and then sister chromatids (meiosis II) are segregated without any intervening DNA replication phase. These two divisions are followed by a differentiation program that includes forespore membrane biogenesis and production of four mature haploid spores (gametes) that are enclosed in an ascus UTP and T7 RNA polymerase. The act1+ riboprobe was used to detect act1+ transcript as an internal control for normalization during quantification of the RNase protection products.Total RNA was extracted using a hot phenol method as described previously . Gene exmfc1+ , pSKmca1+ [mca1+ , pSKctr4+ [ctr4+  and pSKa+ [act1+  were useTo determine the steady-state protein levels of Mca1-TAP or its mutant derivatives and α-tubulin, whole cell extracts were prepared using a trichloroacetic acid (TCA) extraction method . Equal aIn vivo cross-linking of proteins was performed by incubating cell cultures with 1% formaldehyde for 20 min at the indicated time after meiotic induction. After formaldehyde-mediated cross-links and neutralization with glycine, cell lysates were prepared by glass bead disruption in lysis buffer containing 100 mM HEPES-KOH pH 7.5, 1% Triton X-100, 0.1% Na-deoxycholate, 1 mM EDTA, 140 mM NaCl, 2X cOmplete ULTRA Tablets , 1 mM phenylmethylsulfonyl fluoride, 50 mM NaF and 0.2 mM Na3VO4, as described previously [12, immunoprecipitation was performed using protein G Sepharose beads that were coupled to a monoclonal anti-myc antibody . Handling of beads, including washings and elution, reversed cross-linking, and DNA precipitation were performed as described previously [mfc1+, cuf2+, and ctr4+ promoter or coding regions. Primers for ChIP assays were designated by the name of the gene, followed by the position of their 5’ ends relative to that of the translational start codon: mfc1-183 (5’-GTATCGCTAAACTCCGAGGATATAAGTG-3’), mfc1-32 (5’- GAAGATTGAGAATGATGAGAATATATATATCATTTGC-3’), mfc1+875 (5’-TCGTTGGCACTGTTTATGGA-3’), mfc1+960 (5’-TCCCGAAGTGAAGTGGTATTG-3’), cuf2-1139 (5’-TCAGCATCTAGCAGCAAATATACA-3’), cuf2-999 (5’-CGAAGTGATTTCATCAAATTAAGGAACG-3’), ctr4-737 (5’-GAAATGTCACTGTTTGTGATGCTG-3’), and ctr4-584 (5’-CAGCTCTTTTACACGGCAATAATAC-3’). Mca1-TAP, Cuf1-Myc12 or RNA polymerase II density at mfc1+, cuf2+, and ctr4+ genes was calculated as the enrichment of specific genomic mfc1+, cuf2+, and ctr4+ DNA regions relative to a 18S ribosomal DNA coding region in which no functional TCGGCG or CuSE element was present. The primers (denoted 18S-a and 18S-b) that were used to amplify a 18S ribosomal DNA region were described previously [eviously . Sampleseviously , 35. Quamfc1+ mRNA levels in response to low concentrations of copper  and pat1-114/pat1-114 mca1∆/mca1∆ diploid cells expressing the indicated integrative plasmid  were induced to undergo synchronous meiosis in the presence of the copper chelator TTM (150 μM) or CuSO4 (25 μM). Subsequently, total RNA was isolated from culture aliquots taken at different time points. In the case of mca1∆/mca1∆ cells expressing Mca1 or Mca1-TAP, mfc1+ transcripts were initially detected after 3 h of meiotic induction under low copper. These observations contrasted with the absence of significant induction of transcription of mfc1+ mRNA in cells harboring an empty plasmid at the 3-h time point under similar conditions (mfc1+ mRNA levels reached high levels after 7 h of meiotic induction in mca1∆/mca1∆ cells expressing an untagged or a TAP-tagged version of Mca1 (7.2-fold) in comparison with cells transformed with the vector alone (mfc1+ mRNA in mca1∆/mca1∆ cells expressing Mca1 or Mca1-TAP was similar to that observed in the case of mca1+/mca1+ (control) cells, except that the magnitude of induction of mfc1+ mRNA was modestly higher   . Under cMca1-TAP .mca1∆/mca1∆ cells, it conferred copper starvation-dependent regulation of mfc1+ expression in a fashion similar to that of the untagged Mca1 protein. This observation was taken as evidence that Mca1-TAP retained wild-type function. Using mca1∆/mca1∆ cells expressing Mca1-TAP, we first determined the steady-state protein levels of Mca1-TAP over a time period of 1 to 7 h after meiotic induction. Results showed that Mca1-TAP levels were constitutively present irrespective of the cellular copper status . Only very weak levels of cuf2+ promoter fragments were immunoprecipitated  of Pol II [pat1-114/pat1-114 mca1∆/mca1Δ cells harboring an empty integrative plasmid or expressing untagged mca1+ were synchronously induced into meiosis. Immediately before their passage to meiosis, cell cultures were treated with TTM (150 μM) or CuSO4 (25 μM). Aliquots of cell cultures were taken 1, 5, and 7 h after meiotic induction and cells were fixed by formaldehyde treatment for ChIP assays. Primers that hybridized immediately upstream (positions -183 to -32) and at the 3’ end of mfc1+ (positions +875 to +960) coding region were used for qPCR analysis (mfc1+ locus was highly enriched in response to copper starvation conditions and was negligible or absent under copper-replete conditions (mfc1+ (positions -183 to -32) relative to a control 18S ribosomal DNA coding region after 1, 5, and 7 h of meiotic induction (mfc1+ (positions +875 to +960) coding region relative to a 18S ribosomal DNA region reference (mfc1+ transcribed region in vivo requires the presence of the transcription factor Mca1 in response to low concentrations of copper.The RNA polymerase II (Pol II) is a fundamental multi-subunit enzyme that transcribes numerous genes into mRNA in eukaryotic cells . Generalf Pol II . pat1-11analysis . Resultsnditions . In coppnduction . Under teference . Taken tctr4+ mRNA levels are induced in a Cuf1-dependent manner in cells proliferating in mitosis under conditions of copper starvation [ctr4+ mRNA is not detected because its expression is dependent of Cuf1 [ctr4+ as a control gene known to be induced under copper-limiting conditions  immunoprecipitated only background levels of mfc1+ promoter region  under copper-limiting conditions. In contrast, in cells undergoing a transition from low to high copper, Pol II was absent from the ctr4+ locus  [151 and extending to residues Leu299 and Gly326, respectively. The rationale for investigating these 2 mutant forms of Mca1 was the fact that the first deleted region (residues 151–298) contains 2 potential metal-binding motifs (Cys163-X-Cys-X-His165 and Met234-X3-Met238). The resulting C-terminal portions of Mca1 (residues 299–697 and 326–697) were fused in-frame to the DNA binding domain of Mca1 (residues 1–150)   expressed in mca1∆/mca1∆ cells, elevated copper concentrations resulted in a strong repression of mfc1+ mRNA expression  . Becauses 1–150) . Becausenduction . When the point) . In the pression .mfc1+ promoter in vivo, ChIP assays were performed in pat1-114/pat1-114 mca1∆/mca1∆ cells expressing either an untagged or a TAP-tagged version of Mca1 (wild-type or the indicated mutant version). Enrichment levels of Mca1, Mca1-TAP, Mca1DBD-299-697-TAP, and Mca1DBD-326-697-TAP proteins were assessed at the mfc1+ promoter after 1 and 7 h of meiotic induction and compared to enrichment levels of a 18S ribosomal region reference. Results of ChIP assays showed that chromatin enrichment levels by Mca1-TAP and Mca1DBD-299-697-TAP were similar , regardless of the copper status  with the monoclonal anti-RNA Pol II antibody (isotype IgG) that was used for immunoprecipitation of Pol II bound to chromatin. mca1∆/mca1∆ cells expressing untagged Mca1, Mca1DBD-299-697, and Mca1DBD-326-697 were synchronously induced into meiosis and treated with either TTM (150 μM) or CuSO4 (25 μM). Aliquots of cultures were analyzed for their ability to activate mfc1+ transcript levels in response to low concentrations of copper. Results showed that mca1∆/mca1∆ cells expressing untagged Mca1 and Mca1DBD-299-697 proteins conferred copper starvation-dependent activation of mfc1+ expression in a manner similar to that of TAP-tagged Mca1 and Mca1DBD-299-697 proteins   expressed in mca1∆/mca1∆ cells, mRNA levels of mfc1+ remained very low under copper-replete conditions  . In the nditions . Given tnditions .mca1∆/mca1∆ cells expressing Mca1 and Mca1DBD-299-697, association of Pol II with the mfc1+ locus was enriched 43.0- and 38.2-fold, respectively, relative to a 18S ribosomal region reference  were similar to those in mca1∆/mca1∆ cells containing an empty vector (8.9-fold)  . We ther in vivo . Howeverf copper . Under c alleles .mfc1+ expression under low copper conditions, truncations were created from the C-terminal end of a functional Mca1-TAP protein  or CuSO4 (25 μM). At the indicated times after meiotic induction, total RNA was isolated from aliquots of cultures and assayed for copper-dependent regulation of the mfc1+ copper-responsive transcript to determine whether the C-terminal end was important for Mca1 function in vivo. In the case of mca1∆/mca1∆ cells expressing Mca1 1-600-TAP under low copper conditions, mfc1+ mRNA levels were first detected at 3- and 5-h time points. RNA levels reached a maximum 7 h after meiotic induction, exhibiting a 15-fold up-regulation compared with mfc1+ transcript levels observed at the same time point (7 h) under copper-replete conditions  or CuSO4 (25 μM). Aliquots of cultures were retrieved after 1 and 7 h of meiotic induction and ChIP assays were performed to assess the levels of mfc1+ promoter occupancy by Mca1-TAP, Mca1 1-600-TAP, and Mca1 1-570-TAP proteins. Results showed that the mfc1+ promoter was bound by Mca1 1-600-TAP  in a manner similar to that observed for Mca1-TAP   . In the f CuSO4) . Notablyof CuSO4 . The assof mfc1+ . To verior CuSO4 .mfc1+ in the presence of TTM (150 μM) or CuSO4 (25 μM). Steady-state transcript levels of mfc1+ were analyzed 1, 3, 5, and 7 h after meiotic induction. In the presence of TTM, cells expressing mca1+ and mca1 1–600 alleles exhibited maximal expression of mfc1+ transcripts that was induced 23- and 25-fold, respectively, compared to their levels of expression in copper-treated cells (7-h time point)  conditions compared to transcript levels of wild-type Mca1 under the same experimental conditions (7-h time point). Furthermore, the weak levels of mfc1+ transcript in this mutant (Mca1 1–570) were similar to those observed in the case of cells transformed with plasmid alone  that was used to selectively pull down chromatin bound by Pol II. We examined the individual contribution of each version of the transcription factor  in the regulation of e point) . In the id alone .mca1+, mca1 1–600, and mca1 1–570 alleles by RNase protection assays to obtain further indication that untagged Mca1, Mca1 1–600, and Mca1 1–570 proteins were expressed in mca1∆/mca1∆ cells. Results showed that wild-type and mutant mca1 constructs were clearly expressed, with transcripts constitutively detected for each indicated allele regardless of cellular copper status  in mca1∆/mca1∆ cells expressing mca1+ and mca1 1–600 alleles. Consistent with the levels of mfc1+ mRNA that were high under low copper conditions at the 7-h time point, levels of Pol II enrichment were higher in cells that had been exposed to TTM after 7 h. Data showed 38.6- (for mca1+) and 40.0-fold (for mca1 1–600) enrichment at the mfc1+ locus relative to a 18S ribosomal DNA sequence reference  and meiotic time points  are dispensable for Pol II recruitment to chromatin.To confirm that Mca1 and Mca1 1–600 affected transcription eference . In the fter 7 h . In factof mfc1+ . When mee points . Taken tmfc1+ expression under the control of different Mca1 mutants, we hypothesized that residues 299 to 600 of Mca1 were required for transcriptional activation of mfc1+ expression. Accordingly, disruption of this region would result in poor expression of mfc1+ under copper starvation conditions. To test this hypothesis, we deleted the amino acid region 299 to 600 of Mca1-TAP  and 299 to 600-TAP of Mca1 (denoted mca1DBD-299-600-TAP) was created to test whether it mediated proper and timely control of mfc1+ gene expression as a function of copper availability. The experiments were set by expressing mca1+-TAP, mca1 1–298+601-697-TAP, and mca1DBD-299-600-TAP alleles into pat1-114/pat1-114 mca1∆/mca1∆ cells that were synchronously induced into meiosis in the presence of TTM (150 μM) or CuSO4 (25 μM). Aliquots of cell cultures were taken 1, 3, 5, and 7 h after meiotic induction, and steady-state levels of mfc1+ mRNA were analyzed by RNase protections assays. Under low copper conditions (TTM), maximal induction of mfc1+ was primarily observed in cells expressing mca1+-TAP and mca1DBD-299-600-TAP alleles after 7 h of meiotic induction (mfc1+ remained low (96% reduction) in TTM-treated cells expressing mca1 1–298+601-697-TAP or an empty vector  or CuSO4 (25 μM). Aliquots of cultures were retrieved at distinct time points after meiotic induction, and steady-state levels of mfc1+, mca1+, and act1+ mRNAs analyzed by RNase protection assays. In the case of cells expressing untagged mca1+ and mca1DBD-299-600 alleles, mfc1+ transcripts showed an expression profile similar to that observed in the case of cells transformed with mca1+-TAP and mca1DBD-299-600-TAP   and mca1DBD-299-600 (34.8-fold) than those observed in cells expressing mca1 1–298+601–697 (6.1-fold) after 7 h of meiotic induction  . These enduction . In contnditions . Resultsd region . Taken tS. pombe cells. These proteins are Ctr4, Ctr5, Ctr6, and Mfc1 [ctr4+, ctr5+, and ctr6+ transcripts that are regulated by Cuf1, the induction of mfc1+ gene expression is primarily dependent of Mca1 [mfc1+ promoter was analyzed by ChIP assays, results showed that maximal transcriptional induction of mfc1+ was observed in response to copper deficiency and that Mca1 was constitutively bound to the mfc1+ promoter irrespective of changes in copper concentrations. Additional mfc1+ ChIP analysis showed that optimal induction of mfc1+ transcription coincided with maximal chromatin occupancy by RNA Pol II under low copper conditions. In contrast, there was a lack of RNA Pol II recruitment at the mfc1+ locus in response to excess copper.Four proteins have been identified to ensure copper transport in meiotic and Mfc1 . The hetand Mfc1 . In the and Mfc1 . Ctr6 seand Mfc1 , 44. Ctrand Mfc1 . Mfc1 is of Mca1 . When thmfc1+ was reminiscent of the situation observed for other members of the Zn2Cys6 binuclear cluster family of transcription factors. In S. cerevisiae, the zinc cluster transcriptional activator Put3 is constitutively bound to its DNA-recognition sites [S. cerevisiae Gal4 protein is another example of zinc cluster transcription factor that is constitutively bound to cis-acting regulatory elements upstream of the GAL genes when galactose is present as the sole source of carbon [GAL genes by Gal4. In the absence of galactose, the activity of DNA-bound Gal4 is inhibited by its association with the transcriptional repressor Gal80 [GAL genes [mfc1+ in response to copper deficiency occurred only during meiosis but not in cells undergoing mitotic growth. This observation raises the possibility that a meiosis-specific transcriptional inducer may trigger an active state of DNA-bound Mca1. An alternative possibility is that a meiosis-specific factor may inactivate an inhibitory partner of Mca1. In both cases, this would result in the freeing of Mca1 from an inactive state, resulting in transcriptional activation of mfc1+ to occur during specific stages of the meiotic differentiation program. This mechanism would require the meiosis-specific transcriptional inducer to respond to changing environmental copper concentrations because its function is required to induce a switch in Mca1 transcriptional activity to regulate mfc1+ expression as a consequence of copper starvation. Another potential mechanism could be that copper-dependent alterations in Mca1 activity might arise from the formation of a heterodimer complex between Mca1 and a second related Zn2Cys6 cluster transcription factor.The fact that Mca1 was constitutively bound to its target DNA sites upstream of on sites , 46. In on sites . Accordif carbon . The DNAor Gal80 . ConversAL genes . In the mfc1+ gene in response to low copper concentrations. Interestingly, this internal region of Mca1 could be aligned with a region encompassing two inhibitory domains, called ID2 and ID3, that have been identified in the S. cerevisiae Gal4 protein [S. cerevisiae Gal4, the transcriptionally active form of DNA-bound Gal4 interacts directly with the SAGA co-activator-histone-modifying complex, specifically with the Tra1 subunit [S. cerevisiae, one can envision that activation of the transcriptional properties of DNA-bound Mca1 may also involve successive series of interactions with components of SAGA, the fission yeast Mediator complex, and the RNA Pol II, leading to the formation of a competent RNA Pol II holoenzyme for regulated expression of mfc1+.We have identified an internal region (residues 299 to 600) of Mca1 that was required for RNA Pol II-dependent timely activation of the meiotic  protein , 22. Alt subunit , 52. Oth subunit . Based omfc1+ gene expression under low copper conditions. As observed in the case of cells expressing the wild-type protein and mutant cells expressing the mca1DBD-299-697 allele in the presence of copper, results showed lack of inducing mfc1+ transcription. These results suggested that the ID1-like region of Mca1 was not required for maintaining Mca1 transcriptionally inactive under copper-replete conditions. The bulk of these observations led us to conclude that ID2- and ID3-like domains but not the ID1-like region, could be considered as a middle homology region (MHR) with a role in regulating the transcriptional activity of Mca1.Adjacent to the internal ID2- and ID3-like domains of Mca1, an ID1-like region encompassing amino acid residues 151 to 298 was removed (Mca1DBD-299-697 mutant) to test whether this deletion would affect the function of Mca1. Results showed that the Mca1DBD-299-697 mutant protein was active and yielded appropriate timely meiotic induction of mfc1+ gene expression in a Mca1-dependent manner. In the case of the copper-sensing transcription factor Cuf1, a highly conserved C-terminal motif containing the Cys328-X-Cys330-X3-Cys334-X-Cys336-X2-Cys339-X2-His342 sequence (termed C-rich) constitutes its copper-sensing region [mfc1+ gene expression through a mechanism different from that of Cuf1. Within the internal region of Mca1 that encompasses amino acid residues 299 to 600, two potential metal-binding motifs (Cys426-X3-Met-His-X3-His478 and Met476-X-Met478) are present. We have examined the potential role of these motifs in copper starvation-dependent regulation of mfc1+ by generating mutant alleles of mca1+ in which all of the Cys, Met, and His residues had been mutated to alanines. Each Mca1 mutant protein containing either the Ala426-X3-Ala-Ala-X3-Ala478 or Ala476-X-Ala478 mutated motif had no effect on the expression of the mfc1+ gene as compared to that of TTM-mediated activation of mfc1+ transcription in cells expressing a wild-type mca1+ allele Click here for additional data file.


Drug-induced sleep endoscopy (DISE) is a diagnostic tool to assess the upper airway of snorers and obstructive sleep apnea patients in conditions that mimic natural sleep. Although DISE appears simple and similar to awake endoscopy, there are many aspects that need to be standardized in order to obtain reliable and reproducible information. In this article, we will recommend how to reliably perform DISE, its indications, and how to obtain and interpret the information of the upper airway.  Obstructive sleep apnea (OSA) is a common health problem that is associated with an increase in cardiovascular morbimortality, a decrease in quality of life, and a higher risk of traffic accidents due to hypersomnolence ,2. StandRoutine UA assessment is performed when patients are awake—a state with no UA collapse or oxygen desaturation. In a small percentage of OSA patients, the anatomical causes of the obstruction are obvious . However, for most patients, the cause is not so obvious, as they may have long soft palate, a relatively large tongue with grade 1 tonsils, or previous tonsillectomy. Therefore, it is of utmost importance to understand the UA behavior during sleep so that tailor-made treatment can be decided for every patient. In the late 1970s, evaluation of the UA during natural sleep was proposed . UnfortuSince the first publication on DISE , severalIn the European position paper on DISE, and its later update, Ear, Nose and throat (ENT) experts on DISE put in their collective opinion and recommended possible set-up and techniques for DISE to be reliably practiced in different centers ,8. DISE must be performed in a room where all the basic resuscitation equipment  are available, because safety is of utmost importance. The room should also be quiet and dark.In order to perform DISE, the patient should be monitored with electrocardiogram (ECG) and pulse oximeter. Monitoring of sedation depth such as Bi-spectral index (BIS) is highly recommended, as the BIS level of sedation should be between 70 and 50 when the UA is evaluated in adults . EvaluatThe thinnest possible fiber endoscope, ideally with working channel to aspirate secretions, is recommended. The authors also recommend a recording system for video and sound, if possible. The recording is useful, as the videos can be replayed to the patients to help them understand their problem better as well as the potential difficulty in addressing the obstruction. The videos may also be useful in the future if the results of the UA surgery do not achieve the desired outcomes.Based on the literature, many drugs  are used, either alone or in combination, in order to achieve the ideal level of sedation . All of It is recommended to titrate the TCI-propofol pump slowly to achieve the ideal level of sedation . According to Heiser et al. and our personal experience, this level of sedation is achieved when the brain concentration is approximately 3 µg/mL . In ordeDISE is not a painful technique, therefore local anesthesia of the nose is not necessary. Neither is nasal decongestion . AntisecThe patients are usually observed in supine decubitus position, because this is the position where most of the events occur. However, assessment of the UA in a lateral position does give additional information, especially for those patients that sleep mostly in a lateral decubitus position. If the patient’s history suggests that he or she should be assessed in a lateral decubitus position, it may be easier to start DISE in this position, including doing the necessary maneuvers, before changing to supine position. Although the initial study by the de Vries group noted that the UA findings were similar in lateral decubitus compared with supine decubitus with the head turned to one side , a recenIt is very common for patients to open their mouths during DISE, as they usually do at home. If the mouth is open, the tongue may move backward, pushing the soft palate and further obstructing the UA. Changes to the areas and pattern of obstruction can be observed by just closing the mouth. This maneuver  is different from the Esmarch maneuver, which gently pulls the mandible forward to simulate the effect of a mandibular advancement device (MAD). As showed by the Antwerp group, maximum advancement of the mandible does not represent what a MAD can achieve . Other tWe have previously discussed the backward movement of the tongue that pushes the soft palate causing velum collapse. The Esmarch maneuver may be useful to appreciate and differentiate the obstruction related to the tongue and soft palate. Sometimes velar collapse can contribute to secondary tongue or epiglottis collapse. It has been reported that not all UA collapses observed during DISE need to be addressed to achieve a successful result ,27. It iThe UA is observed once the desired sedation level is achieved, when the patient does not respond to verbal stimuli, and when a BIS signal of between 70 and 50 is reached. It is better to begin the observation at the upper part of the airway just below the choana, in order to see the palate and how it closes. Sometimes there may be tongue base or epiglottis collapse while the palate is still open. Most of the time it is impossible to see the tongue base and epiglottis, as the soft palate is closed. After observing the soft palate for 1–2 min, the scope can be advanced downward to observe the rest of the UA. After observing every level, we can proceed with the maneuvers. DISE should take approximately 15–30 min. Longer observation is not useful, as the UA will be full of saliva due to the inhibition of deglutition by propofol . The events that must be observed are the areas of vibration and collapse as well as the shapes of the collapse. For proper assessment of the shapes of obstruction, the tip of the endoscope should be in the middle of the UA . Unfortunately, there is no consensus on the ideal classification. All of them have their own advantages, but none is perfect. Sometimes it can be difficult to categorize the UA findings for the patient as the areas or shapes of collapse can change during the test. Although there is no need to use a classification system to understand the UA behavior, or to choose a tailor-made treatment for each patient, a standardized classification method is of utmost importance to compare findings between patients and results of different types of surgery. Due to its simplicity, a modified VOTE classification was recommended in the updated position paper on DISE . ModificDISE is a diagnostic tool that assesses the areas of vibration and obstruction of the UA. It should be performed in patients with sleep-disordered breathing, as this information is important for treatment. Common sense is essential to adjust both the patient and the media singularities. It is also important to understand that DISE does not assess the severity of the disorder. Before DISE, it is essential for the patient to have a complete polysomnography (PSG) or a simplified sleep polygraph. Some aspects of the UA anatomy of the patient are better observed while awake. Therefore, a complete awake UA examination is also important to help decide the treatment for the patient. As recommended by the European position paper, DISE should be performed for simple snorers and OSA patients when this information is considered important . For exaContraindications include patients for whom DISE cannot be safely performed, such as those with American Society of Anesthesiologists (ASA) class 4, pregnancy or with an allergy to the drugs. The last contraindication should be very uncommon, because if the patient is allergic to propofol then midazolam or dexmedetomidine can be used instead. We strongly believe that a high AHI is not a contraindication in DISE. Although the first-choice treatment for these patients is CPAP, those that cannot tolerate it still deserve an alternative treatment that may help decrease the severity of OSA. DISE will give important information in helping to choose the treatment. DISE is a very useful test, but in order to do it reliably, there are some important tips to consider:If DISE is not performed in an operating room, check to make sure that the basic resuscitation equipment is available .The level of sedation is crucial. The patient should not respond to verbal stimuli but still be able to respond to pain. BIS level should be between 70 and 50. The median TCI concentration of propofol is 3.2 µg/mL. The level of sedation cannot be achieved too quickly . If propofol is injected in bolus too quickly, the patient will be over-sedated, inducing severe UA collapse without snoring. Ideally, the UA should be observed while the patient is snoring. Although uncommon, some patients do not snore significantly. The findings of the UA should still be reliable as long as there is stable respiration at a correct BIS level. Spend more time observing the UA. If there is too much saliva it will be difficult to observe the shapes of the collapses. Aspiration of secretions with a working channel through the endoscope is the best option. If that is not possible, then careful suction with a canula through the mouth or nose can be done. We must be very careful not to injure the mucosa because proper DISE assessment cannot be done in the presence of blood. Be patient, as aspiration may also arouse the patient. The Esmarch maneuver should still be performed in every patient, even when there is no tongue base collapse or when MAD is not considered a treatment option. One must remember that there are different types of tongue base , and theAlthough there is no consensus, a classification system is useful to report the findings. It will help to compare the results between your patients and to learn from the experience of other centers.We should report the level of sedation, lowest oxygen saturation, drug used for sedation (including the delivery mode and the dose used to achieve sedation target level), UA findings, and maneuvers performed during DISE. The updated European DISE position paper provides a useful template. Degree of obstruction can be: 0, no vibration obstruction less than 50%; 1, partial obstruction or vibration; or 2, complete obstruction. Use X if it is not possible to watch that area. DISE is a useful tool to watch the UA of patients with snoring or OSA in a state that mimics natural sleep if the sedation is performed carefully. These findings help to decide the best treatment for each patient when CPAP is not considered or tolerated. To obtain as much information as possible, it is important to perform maneuvers that modify the UA. Nevertheless, DISE represents a small part of the night, mostly what happens in N2, it cannot give information about REM sleep phase.


The balance between excitation and inhibition in neuronal circuits has drawn moreand more attention in recent years, due to its proposed multifaceted functionsin the normal neural circuit as well as its potential roles in the etiology ofmany neurological disorders. Here, we discuss the importance of clearly definingexcitation/inhibition by experimental measurements and the implications of somerecent studies to our understanding of the regulation of excitation/inhibitionat the neuronal level. Comment on: He HY, Shen W, Zheng L, Guo X, Cline HT. Excitatory synapticdysfunction cell-autonomously decreases inhibitory inputs and disrupts structural andfunctional plasticity. Nat Commun. 2018;9:2893. doi: 10.1038/s41467-018-05125-4. PubMed PMID: 30042473; PubMed Central PMCID:PMC6057951. https://www.ncbi.nlm.nih.gov/pubmed/PMC60579511 Experimental evidence also supports the idea that balanced excitation andinhibition within neural circuits facilitates their function,24 and that failure to maintain E/Ibalance underlies circuit dysfunction seen in many neurological diseases. Nevertheless,how a balance of excitatory to inhibitory inputs is established and subsequentlymaintained remains a subject of debate. Recent studies suggest that multiple cellularmechanisms contribute to the regulation of E/I balance.Neurons and circuits coordinate their excitatory and inhibitory inputs to establish andmaintain a constant excitation/inhibition (E/I) ratio that is thought to be essentialfor circuit function and stability. Theoretical modeling demonstrated that wheninhibition tightly matches excitation and tracks it on milliseconds time scale in theneural network, it provides great advantage to the precision and efficiency of neuronalcoding mechanisms.5 Furthermore, different subtypes of inhibitory neurons can assume a differentvalence of plastic changes in response to experience.7 The I (inhibition) in E/I canmean very different things. Sometimes it refers to a subset of the inhibitory inputs(as examined in many studies using transgenic mouse line that focuses on subtypes ofinhibitory neurons). Sometimes it refers to ALL inhibitory inputs a cell receives(as in cases when spontaneous or sensory-evoked synaptic activity was examined). Thetemporal window over which the excitatory and inhibitory synaptic currents areincluded in the E/I measurement can also vary across studies. Sometimes it is summedover a relatively wide temporal window (hundreds of milliseconds), such as shown invisual cortical neurons.8 Sometimes it is confined to a very narrow temporal window with delays onseveral milliseconds scale, as is the case in auditory and somatosensory corticalneurons.10 Another question concerns the method used to measure E/I. Ismeasurement of spontaneous synaptic events (miniature excitatory postsynapticcurrent [mEPSC] and miniature inhibitory postsynaptic current [mIPSC]) sufficient toreflect E/I or should evoked events be measured? Although E/I balance recorded byspontaneous synaptic currents may largely agree with E/I measured by evoked synaptic activity,11 measuring E/I by recording compound excitatory and inhibitory synapticcurrents in vivo evoked by sensory stimulation may be more physiologically relevant,since this reflects the outcome of the coordinated network activity. On the otherhand, recording spontaneous inhibitory and excitatory synaptic currents, andsimilarly, quantifying excitatory and inhibitory synaptic markers post hoc, revealsglobal information about average inputs to the neuron, independent of which inputsare activated by a particular stimulus. Likewise, optogenetic or electricstimulation in brain slices would potentially evoke all synaptic inputs within thepathway but not necessarily reflect the full complement of synaptic inputs evoked bysensory stimulation.In the literature, E/I is often referred to in a very broad sense. In most neuronsstudied, certainly the most intensively studied cortical and hippocampal neurons,inhibitory inputs that one cell receives usually originate from a variety ofinhibitory neurons, which in turn receive highly diverse inputs.1 while the balance of E and I at the level of single neurons and circuits in amore general sense may safeguard circuit stability.13 Whether the same or differentE and I circuits serve these different functions is unclear and this ambiguity maycall for more cautious interpretations of experimental results in E/I studies.This is an important point because the measurement, and therefore the definition ofE/I, may pertain to its function. Multiple functions of E/I have been proposed. Forexample, the temporally tightly matched E and I circuits described in sensorycortices can only be measured by sensory-evoked synaptic responses and may beessential for efficient coding of sensory information,14; however, knowledge of how E/I balance is established and whattriggers adjustments of E or I to maintain the balance of E/I remains scarce.Different methods have been used to perturb inputs/outputs of neurons in vivo and invitro, but not all manipulations triggered corresponding adjustment of E and I thatresulted in unchanged E/I ratio, as measured by E and I synaptic inputs.Neurons (and circuits) maintain E/I balance in response to fluctuations of inputactivity11 and in vivo electrophysiological recordings of spontaneous and visuallyevoked responses, as well as visually evoked behavior to assess circuit-leveleffects of manipulating E/I. At the single cell level, interfering with excitatorysynaptic transmission decreased mEPSCs, as expected. Surprisingly, this also led toa cell autonomous decrease in mIPSCs, as well as a decrease in the density ofinhibitory synaptic puncta. Furthermore, both excitatory and inhibitory componentsof visually evoked responses were proportionally decreased in the affected optictectal neurons, suggesting that decreasing excitatory synaptic input induced acell-autonomous down-regulation of inhibitory synaptic input, so that the E/Ibalance was maintained. This was in stark contrast to our previous observation thatdecreasing inhibitory inputs to tectal cells, by expressing a peptide thatinterferes with GABAAR (gamma-aminobutyric acid type A receptor)trafficking into synapses, does not induce a corresponding decrease in excitatory inputs.15 This indicates that maintaining E/I is not an automatic cellular response toany perturbance of either inhibitory or excitatory inputs to the cell but isspecifically induced by changes in the excitatory inputs. This “leading” role ofexcitation over the regulation of E/I is also consistent with the observations thatthe maturation of inhibition trails excitation in sensory cortices duringdevelopment.1618One way to perturb the neuronal inputs is to interfere with synaptic inputs. To testwhether E/I balance can be maintained after perturbing excitatory synaptic inputs,we interfered with AMPAR (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acidreceptor) trafficking into glutamatergic synapses and evaluated the effect of thismanipulation on inhibitory synapses using both electrophysiology and imaging methodsin the visual system of Xenopus tadpoles. This experimental system allows time-lapsemorphological studies to evaluate the effects of manipulating synaptic inputs onindividual neurons,19 Furthermore, changes in synaptic inputs from the same presynaptic PVinhibitory neurons were specific to the Kir2.1-expressing postsynaptic cells,suggesting cell-autonomous regulation of the PV input by a retrograde signal fromthe postsynaptic neuron. In other studies, decreasing postsynaptic spiking incultured neurons induced a homeostatic increase in excitatory synaptic inputs butfailed to affect inhibitory synaptic inputs.21 It is possible that modulatingintrinsic excitability is yet another mechanism that neurons employ to maintain itsinput/output stability, in addition to E/I. In all the above cases, when intrinsicexcitability was perturbed, either excitatory or inhibitory synaptic inputs changedaccordingly, presumably to maintain neuronal output, but rarely did E and I changedsimultaneously, which resulted in disrupted E/I as measured by synaptic inputs.Interestingly, manipulating CaMKIV  activity in individual pyramidal neurons triggered cell-autonomous changes inboth excitatory synaptic inputs and intrinsic excitability, but failed to induce anychange in the inhibitory synaptic inputs,22 also suggesting a dissociation of the co-regulation of E and I synapticinputs when intrinsic excitability was changed.An alternate strategy to probe mechanisms regulating E/I has been to decreaseexcitability, for instance, with potassium channel expression. Expressing Kir2.1 ina subset of layer 2/3 pyramidal neurons reduced inhibitory inputs from PV+ neuronswithout affecting excitatory synaptic inputs.23 As pointed out above, although excitatory inputs and intrinsic excitabilityhave been reported to be co-regulated under certain circumstances,2022 there are also cases when theyare separately regulated.19 It is possible that multiple mechanisms are involved in the maintenance ofinput/output stability. Whether changes in excitatory synaptic inputs and changes inintrinsic excitability should be treated similarly in terms of E/I regulationremains a question. Data from our studies provide strong in vivo evidence thatinhibitory synaptic inputs are regulated cell-autonomously in response to a directdisruption of excitatory synaptic inputs, which maintains the E/I balance similar tothat in the control neurons. It remains to be seen whether intrinsic excitabilitywas also changed in this scenario.These studies highlight the strikingly different effects of modifying excitabilityand excitatory synaptic inputs with respect to regulation of E/I and importantlyindicate that E/I is not maintained through a single consensus mechanism. Bothintrinsic excitability and excitatory synaptic inputs affect neuronal output(spiking), but through different mechanisms. Intrinsic excitability affects theinput-output function, whereas excitatory synaptic input mostly affects the inputs,and both may affect the active membrane properties in local dendrites. Reducedexcitatory input is not equivalent to reduced excitability of the neurons. Reductionin excitability suppresses spiking activity of the neuron but does not preventpostsynaptic depolarization evoked by excitatory synaptic inputs, which allows localCa influx and can trigger downstream signaling pathways.24 hinting that they may also regulate E/I. We investigated the effect ofGluA-CTP expression on E/I in inhibitory neurons. Our study demonstrated that ininhibitory neurons, at both synaptic and cellular levels, cell-autonomous decreasesin inhibitory inputs were induced by decreased excitatory synaptic transmission andsubsequently maintained E/I, similar to that observed in excitatory neurons.11 This indicates that excitatory and inhibitory neurons both maintain E/Ibalance in response to changes in excitatory synaptic input activity. However, themechanisms that excitatory and inhibitory neurons utilize for the maintenance of E/Ibalance may differ. One clue is that Npas4, an immediately early gene induced byneuronal activity, is known to recruit somatic inhibition onto excitatory neurons inresponse to increased neuronal activity. Knocking out Npas4 in somatostatin(SST)-positive inhibitory neurons significantly decreased excitatory synaptic inputsbut not inhibitory synaptic inputs,25 suggesting that the excitatory and inhibitory neurons may employ distinctactivity-dependent programs regulating excitatory and inhibitory inputs.To this day, most studies on E/I focus on excitatory neurons, which is notsurprising, as they execute neuronal coding. Nonetheless, since inhibitory neuronsalso receive both excitatory and inhibitory inputs, it is important to determinewhether they also regulate E/I balance. Studies in hippocampus indicate that boththe excitatory and the inhibitory neurons can adjust their intrinsic excitability inresponse to changes in activity,11 Despite the relatively normal E/I ratio assessed as synaptic currents , the decreased excitatory and inhibitory synapticinputs in tectal neurons following AMPAR trafficking interference significantlycompromised their receptive field properties and ramified extensively throughout thevisuomotor circuit, interfering with visual experience-dependent dendritic arborplasticity, visual receptive fields, and visuomotor behavior. These defects arelikely due to the disruption of the fine temporal balance (match) between thevisually evoked excitatory and inhibitory inputs after interfering with AMPARtrafficking into excitatory synapses,11 suggesting that temporal features also need to be considered when E/I balanceis concerned.Excitation/inhibition has been studied extensively regarding normal neuronal functionand stability, and disruption of E/I has been implicated in many neurologicaldiseases. Yet, the exact meaning of E/I has become rather ambiguous and variesgreatly with context. To dissect the circuits underlying the different functionsproposed for E/I, as well as understand the molecular mechanisms underlying themaintenance of E/I, it is critical to specify the way that E/I is measured. In termsof the functional relevance of E/I balance, multiple aspects of E/I should be takeninto consideration. For instance, although there is abundant evidence suggestingthat E/I balance is necessary for the normal function of neural circuits, fewstudies have explicitly tested whether E/I is sufficient for circuit function. Ourbehavioral data suggest that is not the case.


The liver has a remarkable regenerative capacity enabled by the plasticity of its epithelial cell compartments. Hepatocytes can re-enter the cell cycle to repopulate the hepatocyte pool or transdifferentiate into biliary epithelial cells  in response to injury . BECs foin vitro and further studied in vivo during a DR, induced by DDC-mediated liver injury. While mTORC1 and YAP signaling promoted BEC expansion, and YAP induced hepatocyte-to-BEC transdifferentiation, LGR4/5-mediated WNT/β-Catenin signaling was dispensable for these processes during a DR in vivo. Detailed assessment of YAP and WNT/β-Catenin signaling during different steps of a DR and recovery from DDC-induced injury confirmed that YAP but not WNT/β-Catenin signaling is activated in BECs. It remains unclear why the dependency of BEC organoids on WNT/β-Catenin signaling did not translate in vivo. We cannot exclude that WNT/β-Catenin signaling is activated in BECs during certain conditions that our injury models did not mimic despite availability of RSPO3 and WNT ligands within the DR. However, it is also plausible that the unphysiological niche provided by Matrigel in which BEC-organoids were embedded biased their signaling in our experiments. Nevertheless, besides revealing mTORC1 and YAP as key regulators of a DR, our CRISPR screen also retrieved many common tumor suppressors in cholangiocarcinoma, which is believed to originate from malignant transformed BECs. This suggests that BEC organoids are a robust research tool to study BEC proliferation and formation of a luminal biliary epithelium ex vivo [Recently, we have investigated signaling pathways controlling BEC expansion using a focused CRISPR-based loss-of-function screen in mouse BEC-organoids. MTORC1, YAP signaling and WNT/β-Catenin signaling were the top hits that we identified  ex vivo . Future Besides their important pro-regenerative functions, activated BECs within a DR have been associated with severe liver diseases such as primary sclerosing cholangitis (PSC), primary biliary cirrhosis (PBC) and other cholangiopathies. BECs can secrete pro-inflammatory factors associated with cholangiopathies and peribiliary fibrosis. Moreover, cholangiocarcinoma formation is unfortunately common in a subset of PSC patients and often only diagnosed during advanced stages ,8. WhethOur single cell analysis of EPCAM+ BECs within a DDC-induced DR identified three distinct subsets of BECs in mice . These B


The deployment of Genome-wide association studies (GWASs) requires genomic information of a large population to produce reliable results. This raises significant privacy concerns, making people hesitate to contribute their genetic information to such studies.χ2 statistic in a privacy-preserving manner, without revealing any information other than whether the statistic is significant or not. Specifically, our protocols compute the χ2 statistic, but only return a yes/no answer, indicating significance. By not revealing the statistic value itself but only the significance, our approach thwarts attacks exploiting statistic values. We significantly increased the efficiency of our HE protocols by introducing a new masking technique to perform the secure comparison that is necessary for determining significance.We propose two provably secure solutions to address this challenge: (1) a somewhat homomorphic encryption (HE) approach, and (2) a secure multiparty computation (MPC) approach. Unlike previous work, our approach does not rely on adding noise to the input data, nor does it reveal any information about the patients. Our protocols aim to prevent data breaches by calculating the We show that full-scale privacy-preserving GWAS is practical, as long as the statistics can be computed by low degree polynomials. Our implementations demonstrated that both approaches are efficient. The secure multiparty computation technique completes its execution in approximately 2 ms for data contributed by one million subjects. The goal of a genome-wide association study (GWAS) is to identify genetic variants that are associated with traits. Large-scale sequencing provides reliable information on single nucleotide variants (SNVs). To date, researchers worked mostly on identifying genetic alterations which lead to classification of SNVs and SNPs (single nucleotide polymorphims). Therefore, when we mention SNVs we refer to both frequent SNPs, and less frequent SNVs. A common approach is to divide the population into a disease, and a healthy group based on whether the individual has the particular disease. Each individual gives a sample DNA from which millions of genetic variants  are identified. If a variant is more frequent in individuals with the disease, it will likely be associated with the specific genetic disorder and be classified as a potential marker of the disease.rare genetic disorders. Two recent developments result in a significant increase of the available data for GWAS: First, the development of cheap next generation sequencing (NGS). Second, the creation of distributed genomic databases, which enable pooling of data from many hospitals, and research centers, further increasing the population sizes of the studies by 10-50 times. Several such distributed databases have recently been proposed, including NGS-Logistics  ] either the homomorphic encryption of x or its secret shared value. Masking in the homomorphic or secret shared domain will then be computed as r and r′ random numbers satisfying the following condition: r is selected to be a positive integer number (bounded properly so as to fit the largest possible input sizes our framework can handle), and then r′ is randomly selected in the range [ 1,r) . Afterwards the masked value is revealed by respectively decrypting or opening the calculated value. Depending on the sign of x and y .To the best of our knowledge the state-of-the-art techniques to perform secure comparisons, both in the homomorphic, and in the secret shared domain, require bitwise operations on the secret inputs, which have a high total cost. To allow for a practically efficient implementation of our solution, we consider a masking technique to perform the comparison instead of the bit-decomposition of our inputs. By masking the values we need to compare, we can later securely reveal the masked result upon decryption, since the mask will hide the original secret value. Hence, masking allows us to perform the comparison without revealing the values we want to keep secret. Comparing two values r, and r′, the correctness of this masking-based comparison is straightforward. To ensure preservation of the security and correctness of the masking, we require one of the medical centers to properly select r, and r′ within suitable bounds. Note that this requirement does not increase the level of trust we need to put in the medical centers (nor does it reduce the security of the system). We already trust the medical centers to provide our privacy-preserving system with their correct inputs. Upon selection of the values r, and r′, the medical center in question homomorphically encrypts these values, or secret shares them to the computation servers, along with its own contributed inputs.Given properly selected x−y, when the system is queried multiple times with the same input. However, in our scenario, the proposed system cannot be queried at will. We suggest the calculation of a table listing all possible phenotypes, and all possible mutation positions, which will become public. This table will be computed on updated input data after a fixed time interval. While constructing the table we select r and r′ at random for each contingency table, thus the random values r and r′ will only be used once with certain input values. After the fixed time interval, we expect the input values to be changed, so we repeat the whole setup and select new random values for each contingency table. Hence, by recomputing the table at fixed times and not allowing users to query, we ensure that no information is leaked by our system.The proposed type of masking, which allows us to perform the comparison, could leak information about the secret input to the inequality, which in our case is the difference x−y from the obtained list of masked values. The maximum of this observed list will be close to the bound set for the randomness r times the difference x−y. Hence, by deduction, if we divide the maximum observed masked value by the upper bound on r, we will get a good approximation of the value x−y.Let us for completeness briefly discuss the leakage that occurs if a party observing the masked result of the inequality check can submit multiple queries on the same inputs and obtain the masked values for these queries. If this would be possible, an adversary would be able to approximate the value of r and r′ once per table entry, and keep them thereafter fixed, until the actual inputs to the protocol  change.In the event of a malicious party being able to observe the intermediate values revealed by our approach , and given that this malicious party can trigger multiple computations of the same table entry, one can prevent the aforementioned leakage by selecting the random values Our general approach that applies both to the HE, and the MPC setting is detailed in Algorithm 1. For the technical details on the HE, and MPC methods used, as well as the implementation details of our proposal, we refer the reader to the full version of our paper . For theχ2 test. Then, the computation server will send the result, which is masked with the technique we introduced in the “To solve the problem described in our application scenario with homomorphic encryption we need multiple parties, as indicated in Fig. χ2 value is revealed to the decryptor. If the system would be adapted to reveal the actual χ2 value, the party receiving the encrypted result would first have to authenticate itself to make sure that it is a trusted entity . If this authentication is considered insufficient by the medical centers contributing their data, they could still prevent the authenticated party from being a single point of trust by introducing a multiparty computation to perform the decryption based on a secret shared decryption key. The solution based on homomorphic encryption does rely on the following two security assumptions: The computation server is honest but curious: It will follow the stated protocol to provide the desired functionality, and will not deviate, nor fail to return the results. The computation server can however monitor the result of every operation it performs. This assumption is reasonable for an economically motivated cloud service provider. The cloud is motivated to provide excellent service, yet it would take advantage of extra available information.We want the decryptor to only decrypt the result of the masked comparison. He should not be allowed to see the input values, since he has the key to decrypt them. Therefore, we presume that the communication between the centers, and the computation server is hidden from the decryptor. This can be achieved by performing the communication over authenticated, secure channels. An alternative way to solve this is by introducing the multiparty computation for the decryptor. Each party only has a part of the decryption key, and hence will never be able to decrypt the values of the encrypted contingency table.It is important to note that in this model we trust the decryptor to decrypt the masked values, and post the corresponding correct yes/no value into the public table. Since the decryptor only decrypts masked values, the decryptor can only deduce the yes/no answer which will become public, anyway. No other information about the χ2 statistic we use the FV scheme, introduced by Fan and Vercauteren [For the homomorphic evaluation of the cauteren . Moreovecauteren  in whichcauteren , and relcauteren .n−1 (out of the n) computing parties.To address the challenge of disease gene identification using secure multiparty computation techniques, in the setting described in our application scenario, we deploy MASCOT . We selen (n≥2) that we have at our disposal. Given that the underlying protocol offers security against any coalition of n−1 computation servers, we consider the security of the whole system to increase as the number of computation servers increases. However, the number of computation servers is inversely proportional to the efficiency of the solution. Therefore, we consider that three computation servers is an adequate number of servers, both from an efficiency/plausibility perspective, and from a security perspective. If any two of the three computation servers that we assume get compromised, or otherwise behave dishonestly, or even collude, the solution still guarantees input privacy, and does not accept incorrect results.For our multiparty computation approach, we first need to determine the number of computation servers We assume a preprocessing phase that can take place offline, at any moment prior to the actual protocol execution. This is to create the necessary randomness for the medical centers to contribute their inputs in a secret shared manner to the computation servers. In addition, the preprocessing phase creates authenticated randomness to be used in the online phase, so as to boost the efficiency of computing multiplications on the shares, which requires interaction amongst the servers.The medical centers that wish to contribute their private inputs, first need to agree on a common format for this data . Then, they need to secret share their contingency tables to the three computation servers, which can also be pushed to an offline, preprocessing phase. Given that all contributing medical centers have shared their private contingency tables to the computation servers, the online phase starts. During the online phase the servers perform both local, and interactive secure computations, and they finally reveal per contingency table whether the relationship between a mutation at a certain DNA position, and a phenotype is significant or not, without disclosing further information on the underlying data. A schematic representation of this approach is presented in Fig. Output Delivery, and Input Supply protocols proposed by Damgård et al. [In our setting, we consider the computing parties that actually execute our protocol , different from the parties contributing their inputs , as shown in Fig. d et al. .For both approaches, namely the homomorphic encryption approach, and the multiparty computation approach, we executed the program 10 times per case, and calculated the average execution time for our timing results. To evaluate the scalability of our protocols, we have considered the cases where our system receives data from 20, 40, 60, 80, and 100 medical centers, respectively. We assume each medical center to contribute data of 10000 subjects . Our timing results represent one SNP-phenotype combination , and the proposed solutions scale linearly in the number of SNP-phenotype combinations.χ2 computation. Our presented timings are obtained by running the implementation on a computer equipped with an Intel Core i5-4590 CPU, running at 3.30 GHz.In order to assess the practical performance, and verify the correctness of the selected parameters of the homomorphic scenario, we implemented the privacy-preserving The encryption time does not depend on the number of centers, since the centers can perform the encryption in parallel. The measured encryption time for one contingency table is 17.1 ms. The time to decrypt the result will also not depend on the number of centers participating in the computation. The measured decryption time is 21.1 ms. The timings for the computation server are listed in Table For the homomorphic setup, there is no communication cost during the computations. The communication cost comes from sending values from each of the three parties to the next. We have three points of communication: the public key has to be sent from the decryptor to the medical centers; the encrypted values of the contingency tables have to be sent from the medical centers to the computation server; and the result has to be sent from the computation server to the decryptor. The size of the public key that needs to be sent to the different medical centers is 186 kB. The data needed to send one contingency table to the computation server is 2.1 MB. The communication cost between the medical centers, and the computation server is the number of centers participating times the amount of data needed to send one contingency table. So this communication cost increases linearly with the number of centers contributing to the computation. We only have to send the resulting value from the computation server to the decryptor, which gives a communication cost of 0.54 MB.We have built a proof of concept implementation of our MPC approach using the platform provided by Keller et al.  in SPDZ-We have only considered the online phase of the protocol, as the preprocessing is protocol-independent, and can be executed at any moment, well before the execution of the online phase. We note, however, that the offline phase is also practically efficient, and we refer the reader to Keller et al.  for moreOur experiments were conducted on localhost with three computation servers. Hence, we do not take the network latency into account in the timing results we report. We do present the size of the data that each server has to send, as well as the communication rounds, and we consider this information to be sufficient for the reader to calculate the additional communication cost, based on the available network bandwidth.For all our timing results we have executed our protocol 10 times per case, and calculated the average execution time. The communication cost of the protocol is constant. For our experiments we have established that all input data is shared by one of the computation servers (namely Server 1), instead of the medical centers that would contribute the data in a real setting.In Table From the setup description of both suggested techniques, one can determine the first significant difference between them: in the homomorphic setting, the medical centers only have to encrypt, and send their data to one party, namely the computation server; while for the multiparty computation they have to secret share their data with two or more computation servers. The execution times resulting from our experiments show that the MPC approach is significantly faster than the homomorphic approach. Even if we assume the encryption of the contingency tables by the medical centers to be part of a preprocessing phase, the homomorphic approach will take more than a second to complete its execution, while the computations in the MPC setup take only a few milliseconds. In terms of communication cost, the homomorphic setup has the advantage that it needs no communication during the computations. However, in terms of total amount of data that has to be transferred between the different parties, the MPC setup outperforms the homomorphic setup once more. We therefore recommend the MPC approach, as it is the most efficient out of the two approaches, and it does not rely on the strong assumption of semi-honest parties participating in the protocol.χ2 test) in a privacy-preserving way, using MPC. To this end, we consider an interesting first step to study how we can express, or approximate logistic regression with low degree polynomials. Then, we can deploy MPC for computing them securely, which will yield solutions efficient enough to be used in practice.Having compared the HE, and MPC approaches in a setting addressing the exact same problem, we have established that MPC can provide more efficient solutions with more relaxed security assumptions. Thus, we plan to proceed with future work on computing state-of-the-art statistics used in GWASs (instead of the more simple χ2 test. Our solutions provide provable security guarantees, while being efficient for realistic sample sizes, and number of medical centers contributing data to the studies. Interestingly, our solutions scale logarithmically in the number of subjects contributing data to the study, which means that as GWAS population sizes grow, our approach will remain suitable. We also propose a new masking-based comparison method, and show that in certain application scenarios, such as the GWAS scenario at hand, comparisons can be executed efficiently even in the HE setting, without leaking useful information about the underlying data.Our work shows that, as long as we can express the statistics to be calculated with low-degree polynomials, privacy-preserving GWAS has become practical. We made the first step to efficient privacy-preserving GWAS with the secure calculation of the


The green‐beard effect is one proposed mechanism predicted to underpin the evolution of altruistic behavior. It relies on the recognition and the selective help of altruists to each other in order to promote and sustain altruistic behavior. However, this mechanism has often been dismissed as unlikely or uncommon, as it is assumed that both the signaling trait and altruistic trait need to be encoded by the same gene or through tightly linked genes. Here, we use models of indirect genetic effects (IGEs) to find the minimum correlation between the signaling and altruistic trait required for the evolution of the latter. We show that this correlation threshold depends on the strength of the interaction , as well as the costs and benefits of the altruistic behavior. We further show that this correlation does not necessarily have to be high and support our analytical results by simulations. In thisA problem with the green‐beard effect is that any mutant alleles that produce the advertising trait without providing the helping behavior—a cheater—will cause its bearer to have higher fitness and will, therefore, be selected for , we find that a quantitative genetics framework based on indirect genetic effects is ideally suited to model the green‐beard scenario. Indirect genetic effect models are based on the premise that trait expression is influenced not only by an individual's own genes (direct genetic effects – DGEs) but also by genes expressed in social partners—indirect genetic effects (IGEs) , and there is no genetic correlation between the traits, and when they assort nonrandomly, (b) with or (c) without the genetic correlation between the signaling and the altruistic trait. As the authors pointed out, the evolution of badge‐based altruism is unlikely without any genetic covariance between the behavior and the signaling traits. Here, we build on their model and complement their results by investigating the fourth scenario: when individuals assort randomly (no relatedness), but there is a genetic correlation between the traits. We use an IGE model to specifically focus on the correlation between the signaling and altruistic trait required for the evolution of the latter. We argue that altruistic traits can evolve and persist even in random populations of unrelated individuals if the correlation between the signaling and altruistic trait is above a given threshold. We show that this correlation threshold depends on the strength of the interaction , as well as the strength of social and nonsocial selection and support our analytical results with agent‐based simulations.McGlothlin et al.  briefly 2iz and ia are column vectors describing phenotypes and genotypes  of the focal individual, respectively, e is a vector of residual values , and z′ denotes the mean phenotype of the focal individual's social partners in a group of size N. The square matrix Ψ describes IGEs. Note that IGEs can be affected by interactions among individuals in a nonlinear way, described in  as Δz¯¯=[I-(N-1)Ψ]-1Δa¯¯. Thus, omitting the factor I-(N-1)Ψ-1 leads to the genotypic response to selectionN is the group size, r is relatedness between individuals, and G is an additive variance—covariance matrix , encoded by their corresponding genes . We further assume that the genotypic values are normally distributed around 0. The presence of a green beard  positively enhances the expression of altruism in social partners, which can be captured in matrix form as Ψ=00Ψ0 where Ψ>0. The altruistic behavior (phenotype) of each individual is given by the genotypic value of its altruistic trait  mediated by the signaling of its social partners  and decreases the fitness of its bearer . Thus, we can write social selection and nonsocial selection gradients as r = 0, the response to selection  is the genotypic variance of the signaling trait, G22 = var(aa) is the genotypic variance of the altruistic trait, and G12 = G21 is the covariance between the two. For the altruistic trait to evolve, the response to selection of this trait must be positive, yielding the conditionFilling in fication ppendix Aρ=G12G11G22, we can express a threshold correlation coefficient between signaling and altruistic traits necessary for the latter to evolveAs the correlation coefficient is defined as Nβ has a negative sign, the threshold correlation coefficient is positive if Ψ is positive. If Ψ is negative, the correlation must be negative, and below the threshold. However, altruism can still evolve.Note that as Ψ and social selection strength Sβ. If this threshold is higher than 1, it means that the altruistic behavior cannot evolve in this particular circumstances (parameter space).Figure 4We support our analytical results discussed in the main manuscript with agent‐based simulations carried out in MATLAB and Python.mN individuals randomly assorted into m groups consisting of N individuals each. Initial genotypic values of both the signaling and the altruistic genes are drawn from the bivariate normal distribution with mean of 0, standard deviation of 1/3, and specified correlation between the two. The altruistic behavior (phenotype) of each individual is given by the genotypic value of its altruistic gene , as well as by the level of signaling of its social partners  and the correlations between both the traits. This analytical result is supported by simulations, as illustrated in Figure Equation To support our analytical derivation of the minimal correlation necessary for increasing the genotypic value of the altruistic gene, we simulated a population of 50 groups consisting of 15 interacting individuals each, for a range of correlation values between the signaling and the altruistic trait. The response to selection is calculated as the difference between the mean genotypic values of the parental and the offspring generations. The mean response to selection for each parameter set was calculated from 100 trials. The results of the simulations displayed in Figure 4.2m (number of groups) and N (group size). As expected, after some time, fixation occurred, and genetic variance was lost from the population. Figure m and N . We observed that even in cases when the mean genotypic value of the altruistic trait decreased, the overall expression of altruistic behavior increased due to the increased signaling genotypic values. See Appendix To simulate long‐term evolution, we simulated evolving populations for 500 generations, for various N, number of groups m, and the initial correlation ρ between the signaling and the altruistic trait. Invasion rate is calculated from 200 independent trials, and mean invasion rate and standard deviation are calculated from 50 repeats of 200 evolution trials for each parameter set. Figure mN. However, this trend was not so clear with increasing group size, as the invasion rate slightly increased at the beginning.To investigate the stability of the evolved altruistic population, we let the population evolve for 500 generation and then introduced a single individual with a high genetic value of the signaling, but a low value of altruistic trait—a cheater. We simulated the population for another 500 generations and recorded whether the cheater haplotype invaded the population or was eradicated. We varied the group size 5Most population genetics, as well as game theoretic models analyzing the evolution of altruism assume a binary division of phenotypes (and genotypes as well): altruists and cheaters. While undoubtedly helpful, the biological reality surely differs—most complex and social traits, such as altruistic behavior, are not binary but expressed on continuous scales and the environment likely mediates their expression. IGE models are naturally set up to deal with such situations, offering more realistic insight into many aspects of social behavior. Several social interactions can be formalized and analyzed by these models as easily as the green‐beard scenario. Recently, models of social evolution with continuous traits have been developed Mullon, Keller, and Lehmann , but theIt should be noted, that our approach to study green‐beard scenario is limited by the assumption of mediated, but nondiscriminate altruism toward an individual's social partners. Each individual's level of altruism is determined by its group, and all social partners experience the same benefit from a given individual. However, the same individual would behave differently in a different group. Therefore, it is rather a "group's green beard" than an "individual's green beard" that plays a role, and thus, it could be argued that our model is not the green‐beard model as originally suggested by Dawkins. One possibility to use IGEs while tending to this problem is to consider sequential pairwise interactions between individuals, rather than a simultaneous interaction .5.1Ψ would have to be very strong in comparison with the strength of nonsocial selection. Then, the authors assumed that individuals assort nonrandomly with respect to the signaling trait, with or without the genetic correlation, which lessened the condition on the strength of interaction. In this manuscript, we complement their results, and we explicitly assume that groups are formed randomly (the relatedness is zero) and show that altruism can still evolve, even if both interaction strength Ψ and selection strength Sβ are of the same magnitude.McGlothlin et al.  derived Ψ and selection strength Sβ  the response to selection is always negative, even if both traits are completely correlated .Using IGE models, we were able to determine the necessary correlation between the signaling and the altruistic trait for the latter to evolve Equation . We showWhile we are not aware of any other study investigating the correlation between the signaling and the altruistic trait in the green‐beard scenario, Kirkpatrick and Barton  obtained5.2Nβ var(aa) describes the direct adverse effect of an altruistic trait on the fitness of its carrier. However, if the correlation between the signaling and altruistic trait is strong enough, it may be compensated by the indirect response to selection, described by the first term (N-1)βSΨcov(aaas).Equation (N-1)βSΨvar(as) in Equation Ψ induces a positive response to selection in the signaling trait—the high values of signaling genes are rewarded through eliciting altruistic behaviors from other, leading to positive correlation between genotypic values and fitness. As McGlothlin et al. (Nβcov(aasa), describing the indirect response to selection, which has an adverse fitness effect due to the correlation with altruistic behavior. Thus, while the correlation between traits enhances the evolution of an altruistic trait, it slows down the evolution of the signaling trait. Because IGEs are associated with the altruistic trait and not the genetic correlation between the two, the signaling trait evolves in a positive direction.The first term n et al.  pointed Our agent‐based simulations support the analytical results for the correlation threshold. While the response to selection in a particular population greatly varies, the mean response closely matched the predicted values for given correlations. For correlations above the predicted threshold, the mean response of the altruistic trait is positive, meaning that the offspring's mean genotypic value for altruistic behavior has increased. The mean genotypic value of the signaling trait also increased, for any value of correlation. However, the response decreased with the increasing correlation, as suggested by Equation The manifestation of the altruistic trait (phenotype) depends highly on the population structure and the level of signaling. Interestingly, we observed that even for some parameter sets, where the mean genotypic value of the altruistic trait evolved toward negative values, the mean phenotypic value of altruistic behavior was positive and increasing. This was caused by the evolution of the signaling trait—higher signaling levels increased altruistic behavior, even though the genotypic values evolved in the opposite direction. This points to the importance of distinguishing between the genotypic response to selection derived here, and the phenotypic response to selection derived by McGlothlin et al. . The pheIn our model, the expression of the altruistic trait depends on the overall (absolute) level of signaling, meaning that more social partners would elicit more altruistic behavior from the focal individual. In such a case, whether the individual behaves altruistically or not depends on the size of the group it belongs to. However, it would also be reasonable to assume that the altruistic response depends on the mean, rather than the absolute level of signaling in the group. In such a case, group size would not affect the expression of the trait, and we would not observe the discrepancy between the signs of the phenotypic and genotypic response to selection. In other words, if the mean, not the absolute level of signaling determines the expression of the altruistic trait, the phenotypic and genotypic response to selection should be in the same direction Appendix . The mos5.3A positive response to selection in one generation does not guarantee the long‐term increase in the level of altruism, as the correlation between the traits will also develop with the evolution of the traits. Our simulations of long‐term evolution suggest that the response to selection is positive for a number of generations if the initial correlation is above the calculated threshold Equation . The meaΨ and driven by the evolution of the signaling trait.Interestingly, mean phenotypic values are increasing even for correlations below the threshold, and even when the mean genotypic value is negative, the mean phenotypic value can be positive. This is because the expression of the trait is strongly determined by Jansen and van Baalen  investigIn our model, there is no binary division of phenotypes between altruists and cheaters, and the genotypic values of both traits are continuous and mediated by the phenotypes of social partners. Furthermore, altruistic behavior is mediated by the phenotypes of social partners but is nondiscriminatory—every social partner experiences the same benefit from a particular individual. However, "cheaters" can be simulated as individuals that have high genetic values for the signaling trait, but low genetic values of the altruistic trait.While the Janssen and Goldstone  model isThe utility of the IGE models has been highlighted numerous times (Bijma & Aanen, We complemented our analytical results with agent‐based simulations and confirmed that even in the long term, altruistic behavior can evolve though the green‐beard mechanism and persist in the population. Furthermore, our simulations show that such altruistic populations can be reasonably resistant to the invasion of cheaters. However, we did not assume any recombination between the traits, which could increase the probability of cheaters invading. This, as well as other possible extensions including variable population sizes and mutation events, still need to be investigated.None declared.Data archival location: There are no data to be archived.BT: analyzed the model and wrote the article; RH: supervised the analysis and wrote the article.