ParB-type DNA Segregation Proteins Are CTP-Dependent Molecular Switches.

During cell division, newly replicated DNA is actively segregated to the daughter cells. In most bacteria, this process involves the DNA-binding protein ParB, which condenses the centromeric regions of sister DNA molecules into kinetochore-like structures that recruit the DNA partition ATPase ParA and the prokaroytic SMC/condensin complex. Here, we report the crystal structure of a ParB-like protein (PadC) that emerges to tightly bind the ribonucleotide CTP. The CTP-binding pocket of PadC is conserved in ParB and composed of signature motifs known to be essential for ParB function. We find that ParB indeed interacts with CTP and requires nucleotide binding for DNA condensation in vivo. We further show that CTP-binding modulates the affinity of ParB for centromeric parS sites, whereas parS recognition stimulates its CTPase activity. ParB proteins thus emerge as a new class of CTP-dependent molecular switches that act in concert with ATPases and GTPases to control fundamental cellular functions.

ATP-Driven Separation of Liquid Phase Condensates in Bacteria.

Liquid-liquid phase-separated (LLPS) states are key to compartmentalizing components in the absence of membranes; however, it is unclear whether LLPS condensates are actively and specifically organized in the subcellular space and by which mechanisms. Here, we address this question by focusing on the ParABS DNA segregation system, composed of a centromeric-like sequence (parS), a DNA-binding protein (ParB), and a motor (ParA). We show that parS and ParB associate to form nanometer-sized, round condensates. ParB molecules diffuse rapidly within the nucleoid volume but display confined motions when trapped inside ParB condensates. Single ParB molecules are able to rapidly diffuse between different condensates, and nucleation is strongly favored by parS. Notably, the ParA motor is required to prevent the fusion of ParB condensates. These results describe a novel active mechanism that splits, segregates, and localizes non-canonical LLPS condensates in the subcellular space.

In vivo assembly of bacterial partition condensates on circular supercoiled and linear DNA.

In bacteria, faithful DNA segregation of chromosomes and plasmids is mainly mediated by ParABS systems. These systems, consisting of a ParA ATPase, a DNA binding ParB CTPase, and centromere sites parS, orchestrate the separation of newly replicated DNA copies and their intracellular positioning. Accurate segregation relies on the assembly of a high-molecular-weight complex, comprising a few hundreds of ParB dimers nucleated from parS sites. This complex assembles in a multi-step process and exhibits dynamic liquid-droplet properties. Despite various proposed models, the complete mechanism for partition complex assembly remains elusive. This study investigates the impact of DNA supercoiling on ParB DNA binding profiles in vivo, using the ParABS system of the plasmid F. We found that variations in DNA supercoiling does not significantly affect any steps in the assembly of the partition complex. Furthermore, physical modeling, leveraging ChIP-seq data from linear plasmids F, suggests that ParB sliding is restricted to approximately 2 Kbp from parS, highlighting the necessity for additional mechanisms beyond ParB sliding over DNA for concentrating ParB into condensates nucleated at parS. Finally, explicit simulations of a polymer coated with bound ParB suggest a dominant role for ParB-ParB interactions in DNA compaction within ParB condensates.

Characterizing multimorbidity in ALIVE: comparing single and ensemble clustering methods.

Multimorbidity, defined as having 2 or more chronic conditions, is a growing public health concern, but research in this area is complicated by the fact that multimorbidity is a highly heterogenous outcome. Individuals in a sample may have a differing number and varied combinations of conditions. Clustering methods, such as unsupervised machine learning algorithms, may allow us to tease out the unique multimorbidity phenotypes. However, many clustering methods exist, and choosing which to use is challenging because we do not know the true underlying clusters. Here, we demonstrate the use of 3 individual algorithms (partition around medoids, hierarchical clustering, and probabilistic clustering) and a clustering ensemble approach (which pools different clustering approaches) to identify multimorbidity clusters in the AIDS Linked to the Intravenous Experience cohort study. We show how the clusters can be compared based on cluster quality, interpretability, and predictive ability. In practice, it is critical to compare the clustering results from multiple algorithms and to choose the approach that performs best in the domain(s) that aligns with plans to use the clusters in future analyses.

Spatially Confined π-Complexation within Pore-Space-Partitioned Metal-Organic Frameworks for Enhanced Light Hydrocarbon Separation and Purification.

Ultramicroporous metal-organic frameworks (MOFs) are demonstrated to be advantageous for the separation and purification of light hydrocarbons such as C2H2, C2H4, and CH4. The introduction of transition metal sites with strong π-complexation affinity into MOFs is more effective than other adsorption sites for the selective adsorption of π-electron-rich unsaturated hydrocarbon gases from their mixtures. However, lower coordination numbers make it challenging to produce robust MOFs directly utilizing metal ions with π-coordination activity, such as Cu+, Ag+, and Pd2+. Herein, a series of novel π-complexing MOFs (SNNU-33s) with a pore size of 4.6 Å are precisely constructed by cleverly introducing symmetrically matched C3-type [Cu(pyz)3] (pyz = pyrazine) coordinated fragments into 1D hexagonal channels of MIL-88 prototype frameworks. Benifit from the spatial confinement combined with π-complex-active Cu+ of [Cu(pyz)3], pore-space-partitioned SNNU-33 MOFs all present excellent C2H2/CH4, C2H4/CH4, and CO2/CH4 separation ability. Notably, the optimized SNNU-33b adsorbent demonstrates top-level IAST selectivity values for C2H2/CH4 (597.4) and C2H4/CH4 (69.8), as well as excellent breakthrough performance. Theoretical calculations further reveal that such benchmark light hydrocarbon separation and purification ability is mainly ascribed to the extra-strong binding affinity between Cu+ and π-electron donor molecules via a spatially confined π-complexation process.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression.

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

Can Aromaticity Be Evaluated Using Atomic Partitions Based on the Hilbert-Space?

Aromaticity is a fundamental concept in chemistry that explains the stability and reactivity of many compounds by identifying atoms within a molecule that form an aromatic ring. Reliable aromaticity indices focus on electron delocalization and depend on atomic partitions, which give rise to the concept of an atom-in-the-molecule (AIM). Real-space atomic partitions present two important drawbacks: a high computational cost and numerical errors, limiting some aromaticity measures to medium-sized molecules with rings up to 12 atoms. This restriction hinders the study of large conjugated systems like porphyrins and nanorings. On the other hand, traditional Hilbert-space schemes are free of the latter limitations but can be unreliable for the large basis sets required in modern computational chemistry. This paper explores AIMs based on three robust Hilbert-space partitions - meta-Löwdin, Natural Atomic Orbitals (NAO), and Intrinsic Atomic Orbitals (IAO) - which combine the advantages of real-space partitions without their disadvantages. These partitions can effectively replace real-space AIMs for evaluating the aromatic character. For the first time, we report multicenter index (MCI) and Iring values for large rings and introduce ESIpy, an open-source Python code for aromaticity analysis in large conjugated rings.

Comparison of percutaneous microwave/radiofrequency ablation liver partition and portal vein embolization versus transarterial chemoembolization and portal vein embolization for planned hepatectomy with insufficient future liver remnant.

BACKGROUND: In China, both percutaneous microwave/radiofrequency ablation liver partition plus portal vein embolization (PALPP) and transarterial chemoembolization (TACE) plus portal vein embolization (PVE) have been utilized in planned hepatectomy. However, there is a lack of comparative studies on the effectiveness of these two techniques for cases with insufficient future liver remnant (FLR). METHODS: Patients were categorized into either the PALPP group or the TACE + PVE group. Clinical data, including FLR growth rate, complications, secondary resection rate, and overall survival rate, were compared and analyzed for both groups retrospectively. RESULTS: Between December 2014 and October 2021, a total of 29 patients underwent TACE + PVE (n = 12) and PALPP (n = 17). In the TACE + PVE group, 7 patients successfully underwent two-stage hepatectomy, while in the PALPP group, 13 patients underwent the procedure (two-stage resection rate: 58.3% vs. 76.5%, P = 0.42). There were no significant differences in postoperative complications of one-stage procedures (11.8% vs. 8.3%, P > 0.05) and second-stage resection complication (0% vs. 46.2%, P = 0.05) between the TACE + PVE and PALPP groups. However, the PALPP group demonstrated a shorter time to FLR volume growth for second-stage resection (18.5 days vs. 66 days, P = 0.001) and KGR (58.5 ml/week vs. 7.7 ml/week, P = 0.001). CONCLUSIONS: Compared with TACE + PVE, PALPP results in a more significant increase in FLR volume and a higher rate of two-stage resection without increasing postoperative complications.

The Separability Problem in Molecular Quantum Systems: Information-Theoretic Framework for Atoms in Molecules.

Even though molecules are fundamentally quantum entities, the concept of a molecule retains certain classical attributes concerning its constituents. This includes the empirical separability of a molecule into its three-dimensional, rigid structure in Euclidean space, a framework often obtained through experimental methods like X-Ray crystallography. In this work, we delve into the mathematical implications of partitioning a molecule into its constituent parts using the widely recognized Atoms-In-Molecules (AIM) schemes, aiming to establish their validity within the framework of Information Theory concepts. We have uncovered information-theoretical justifications for employing some of the most prevalent AIM schemes in the field of Chemistry, including Hirshfeld (stockholder partitioning), Bader's (topological dissection), and the quantum approach (Hilbert's space definition). In the first approach we have applied the generalized principle of minimum relative entropy derived from the Sharma-Mittal two-parameter functional, avoiding the need for an arbitrary selection of reference promolecular atoms. Within the ambit of topological-information partitioning, we have demonstrated that the Fisher information of Bader's atoms conform to a comprehensive theory based on the Principle of Extreme Physical Information avoiding the need of employing the Schwinger's principle, which has been proven to be problematic. For the quantum approach we have presented information-theoretic justifications for conducting Löwdin symmetric transformations on the density matrix to form atomic Hilbert spaces generating orthonormal atomic orbitals with maximum occupancy for a given wavefunction.

A Set of New Promising Solid Chalcogenides for Na-Ion Batteries: Yield from the Crystal Chemical, Monte-Carlo and Quantum-Chemical Calculations.

Free crystal space in more than 600 chalcogenide structures taken out from the ICSD has been theoretically analyzed. As a result, wide voids and channels accessible for Na+-ion migration were found in 236 structures. Among them, 165 compounds have not been described in the literature as Na+-conducting materials. These materials have been subjected to stepwise quantitative calculations. The bond valence site energy method has enabled the identification of 57 entries as the most promising ion conductors in which the Na+-ion migration energy (Em) is less than 0.55 eV for 2D or 3D diffusion. The kinetic Monte-Carlo method has been carried out for these substances; as a result, resulting in nine of the most prospective compounds with Na+-ionic conductivity Ϭ≥10-4 S cm-1 at room temperature were selected, for which the density functional theory calculations have been performed yielding six best candidates. Additionally, a logarithmic relationship was established between the values of Em and the diffusion channel radii as well as a linear relationship between Ϭ and the void radius.

The colorful fungi of the Chilean forests: Production, chemical characterization and possible applications of their pigments.

In Chile, as in the rest of the world, only a small fraction of the fungal diversity inhabiting the wide variety of its ecosystems is known. This diversity must hide an inestimable richness of species with interesting biotechnological potential, including fungal pigment producers. Recently, interest in filamentous fungi has increased significantly due to their importance as alternative sources of pigments and colorants that are environmentally and human health friendly. As a result, fungal pigments are gaining importance in various industrial applications, such as food, textiles, pharmaceuticals, cosmetics, etc. The increasing consumer demand for "green label" natural colorants requires the exploration of different ecosystems in search of new fungal species that are efficient producers of different pigment with a wide range of colors and ideally without the co-production of mycotoxins. However, advances are also needed in pigment production processes through fermentation, scale-up from laboratory to industrial scale, and final product formulation and marketing. In this respect, the journey is still full of challenges for scientists and entrepreneurs. This chapter describes studies on pigment-producing fungi collected in the forests of central-southern Chile. Aspects such as the exploration of potential candidates as sources of extracellular pigments, the optimization of pigment production by submerged fermentation, methods of pigment extraction and purification for subsequent chemical characterization, and formulation (by microencapsulation) for potential cosmetic applications are highlighted. This potential use is due to the outstanding bioactivity of most fungal pigments, making them interesting functional ingredients for many applications. Finally, the use of fungal pigments for textile and spalting applications is discussed.

Personalized treatment selection via product partition models with covariates.

Precision medicine is an approach for disease treatment that defines treatment strategies based on the individual characteristics of the patients. Motivated by an open problem in cancer genomics, we develop a novel model that flexibly clusters patients with similar predictive characteristics and similar treatment responses; this approach identifies, via predictive inference, which one among a set of treatments is better suited for a new patient. The proposed method is fully model based, avoiding uncertainty underestimation attained when treatment assignment is performed by adopting heuristic clustering procedures, and belongs to the class of product partition models with covariates, here extended to include the cohesion induced by the normalized generalized gamma process. The method performs particularly well in scenarios characterized by considerable heterogeneity of the predictive covariates in simulation studies. A cancer genomics case study illustrates the potential benefits in terms of treatment response yielded by the proposed approach. Finally, being model based, the approach allows estimating clusters' specific response probabilities and then identifying patients more likely to benefit from personalized treatment.

Clustering blood donors via mixtures of product partition models with covariates.

Motivated by the problem of accurately predicting gap times between successive blood donations, we present here a general class of Bayesian nonparametric models for clustering. These models allow for the prediction of new recurrences, accommodating covariate information that describes the personal characteristics of the sample individuals. We introduce a prior for the random partition of the sample individuals, which encourages two individuals to be co-clustered if they have similar covariate values. Our prior generalizes product partition models with covariates (PPMx) models in the literature, which are defined in terms of cohesion and similarity functions. We assume cohesion functions that yield mixtures of PPMx models, while our similarity functions represent the denseness of a cluster. We show that including covariate information in the prior specification improves the posterior predictive performance and helps interpret the estimated clusters in terms of covariates in the blood donation application.

Tire Wear Chemicals in the Urban Atmosphere: Significant Contributions of Tire Wear Particles to PM2.5.

Tire wear particles (TWPs) containing tire wear chemicals (TWCs) are of global concern due to their large emissions and potential toxicity. However, TWP contributions to urban fine particles are poorly understood. Here, 72 paired gas-phase and PM2.5 samples were collected in the urban air of the Pearl River Delta, China. The concentrations of 54 compounds were determined, and 28 TWCs were detected with total concentrations of 3130-317,000 pg/m3. Most p-phenylenediamines (PPDs) were unstable in solvent, likely leading to their low detection rates. The TWCs were mainly (73 ± 26%) in the gas phase. 2-OH-benzothiazole contributed 82 ± 21% of the gas-phase TWCs and benzothiazole-2-sulfonic acid contributed 74 ± 18% of the TWCs in PM2.5. Guangzhou and Foshan were "hotspots" for atmospheric TWCs. Most TWC concentrations significantly correlated with the road length nearby. More particulate TWCs were observed than model predictions, probably due to the impacts of nonexchangeable portion and sampling artifacts. Source apportionment combined with characteristic molecular markers indicated that TWPs contributed 13 ± 7% of urban PM2.5. Our study demonstrates that TWPs are important contributors to urban air pollution that could pose risks to humans. There is an urgent need to develop strategies to decrease TWP emissions, along with broader urban air quality improvement strategies.

Traditional and Novel Organophosphate Esters in Plastic Greenhouse: Occurrence, Multimedia Migration, and Exposure Risk via Vegetable Consumption.

The migration and risk of organophosphate esters (OPEs) in agricultural air-soil-plant multimedia systems due to plastic film application remain unclear. This study investigates the multimedia distribution of traditional OPEs (TOPEs), novel OPEs (NOPEs), and their transformation products (POPEs) in plastic and solar greenhouses. The total concentration of OPE-associated contaminants in air and airborne particles ranged from 594 to 1560 pg/m3 and 443 to 15600 ng/g, respectively. Significant correlations between air OPE concentrations and those in polyolefin film (P < 0.01) indicate plastic film as the primary source. Contaminants were also found in soils (96.8-9630 ng/g) and vegetables (197-7540 ng/g). The primary migration pathway for NOPEs was particle dry deposition onto the soil and leaf, followed by plant accumulation. Leaf absorption was the main uptake pathway for TOPEs and POPEs, influenced by vegetable specific leaf surface area. Moreover, total exposure to OPE-associated contaminants via vegetable intake was assessed at 2250 ng/kg bw/day for adults and 2900 ng/kg bw/day for children, with an acceptable hazard index. However, a high ecological risk was identified for NOPE compounds (median risk quotient, 975). This study provides the first evidence of the multimedia distribution and potential threat posed by OPE-associated contaminants in agricultural greenhouses.

Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish.

Tissue-to-blood partition coefficients (Ptb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring Ptb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit Ptb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict Ptb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals.

Distribution Control and Environmental Fate of PFAS in the Offshore Region Adjacent to the Yangtze River Estuary─A Study Combining Multiple Phases Analysis.

The Yangtze River Estuary is the terminal sink of terrestrial per- and polyfluoroalkyl substances (PFAS) from the Yangtze River, while the environmental fate characteristics of legacy and emerging PFAS around this region have rarely been discussed. Here, 24 targeted PFAS in seawater, sediments, suspended particulate matter (SPM), and plankton in the offshore region adjacent to this estuary were investigated. The three dominant PFAS in all phases were perfluorooctanoic acid (PFOA, 23.8-61.9%), perfluorobutanoic acid (PFBA, 23.6-42.8%), and perfluoro(2-methyl-3-oxahexanoic) acid (HFPO-DA, 6.1-12.1%), and perfluoro-1-butane sulfonamide (FBSA, 0.1-7.3%) was first detected. The horizontal distributions of PFAS were dependent on salinity and disturbed by multiple water masses, while the vertical variations could be explained by their different partitioning characteristics in the water-SPM-sediment system (partition coefficients, Log Kd and Log Koc) and plankton (bioaccumulation factors, Log BAF). Although physical mixing was the major driver for PFAS settling (>83.7%), the absolute settling amount caused by the biological pump was still high (150.00-41994.65 ng m-2 day-1). More importantly, we found unexpected high Log Kd values of PFBA (2.24-4.55) and HFPO-DA (2.26-4.67), equal to PFOA (2.28-4.72), which brought concerns about their environmental persistence. Considering the increased detection of short-chain and emerging PFAS, more comprehensive environmental behaviors analysis is required urgently.

Polyparameter Linear Free Energy Relationships for Partitioning of Neutral Organic Compounds to Storage Lipids.

Storage lipids are an important compartment in the bioaccumulation of neutral organic compounds. Reliable models for predicting storage lipid-water and storage lipid-air partition coefficients (Kislip/w and Kislip/a), as well as their temperature dependence, are considered useful. Polyparameter linear free energy relationships (PP-LFERs) are accurate, general, and mechanistically clear models for predicting partitioning-related physicochemical quantities. About a decade ago, PP-LFERs were calibrated for Kislip/w at the physiological temperature of 37 °C. However, to date, a comprehensive collection and sufficiently reliable PP-LFERs for Kislip/w and Kislip/a at the most common standard temperature of 25 °C are still lacking. In this study, experimentally based Kislip/w and/or Kislip/a values at 25 °C for 278 compounds were extensively collected or converted from the literature. Subsequently, PP-LFERs were calibrated for Kislip/w and Kislip/a at 25 °C, performing well over 10 orders of magnitude with root-mean-square errors of 0.17-0.21 log units for compounds with reliable descriptors. Furthermore, standard internal energy changes of transfer from water or air to storage lipids for 158 compounds were derived and used to calibrate PP-LFERs for estimating the temperature dependence of Kislip/w or Kislip/a. Additionally, using PP-LFERs, low-density polyethylene was confirmed to be a better storage lipid analogue than silicone and polyoxymethylene in the equilibrium passive sampling of nonpolar and H-bond acceptor polar compounds.

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses.

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

Incomplete partition type II in its various manifestations: isolated, in association with EVA, syndromic, and beyond; a multicentre international study.

PURPOSE: Incomplete partition type II (IP-II) is characterized by specific histological features and radiological appearance. It may occur in isolation or in association with an enlarged vestibular aqueduct (EVA). Among those with IP-II and EVA, a subset has a diagnosis of Pendred syndrome. This study aimed to explore the prevalence of isolated IP-II, IP-II with EVA, and cases with a genetic or syndromic basis in our cohort. METHODS: From a large, multicentre database of dysplastic cochleae (446 patients, 892 temporal bones), those with imaging features of IP-II were examined in detail, including whether there was a genetic or syndromic association. RESULTS: A total of 78 patients with IP-II were identified. Among these, 55 patients had bilateral IP-II and EVA (only 12 with typical Mondini triad), 8 with bilateral IP-II and normal VA, 2 with bilateral IP-II and unilateral EVA, and 13 with unilateral IP-II (9 with unilateral EVA). Among the group with bilateral IP-II and bilateral EVA in whom genetic analysis was available, 14 out of 29 (48%) had SLC26A4 mutations and a diagnosis of Pendred syndrome, 1 had a FOXI1 mutation, and a few other genetic abnormalities; none had KCNJ10 pathogenic variants. CONCLUSION: Bilateral IP-II-bilateral EVA may be seen in the context of Pendred syndrome (SLC26A4 or FOXI1 mutations) but, in the majority of our cohort, no genetic abnormalities were found, suggesting the possibility of unknown genetic associations. IP-II in isolation (without EVA) is favored to be genetic when bilateral, although the cause is often unknown.