Characterization of Amyloidosis in the Gastrointestinal Tract With an Emphasis on Histologically Distinct Interstitial Patterns of Deposition and Misinterpretations.

Amyloidosis can involve the gastrointestinal (GI) tract, and deposition can present with varied histologic patterns that make recognition challenging. This retrospective observational study aimed to characterize the deposition patterns in the GI tract and evaluate key quality metrics, including discrepant cases, to improve recognition and provide insight for accurate diagnosis. Sixty-two patients (195 biopsies) with amyloid involvement of the luminal tract were reviewed. Amyloid subtyping by mass spectrophotometry was available for 59 patients. Immunoglobulin light chain (AL) was the most commonly identified subtype (60%), followed by serum amyloid A (AA; 19%) and transthyretin (ATTR; 16%). 150/195 biopsies (77%) were positive for amyloid deposition, with an average of 2.4 positive biopsies per every 3.1 taken per patient. The sites with the highest yield were duodenum (37/37, 100%) and colon (63/74, 85%). Gastric biopsies were most likely to involve the lamina propria (41/45, 91%, P < 0.001), with the background mucosa showing reactive epithelial changes in almost half of the biopsies (20/45, 44%). Several distinct histologic patterns of interstitial deposition were identified, including muscularis mucosae deposition (n = 40, 27% of positive biopsies), peri-Brunner gland (n = 6, 17% of duodenal biopsies), mass-forming (n = 4, 2.7% of positive biopsies, including 3 suspected cases with localized involvement), collagenous colitis-like (n = 3, 4.8% of positive colonic biopsies), and globular (n = 19, 12.7% of positive biopsies). Congo Red was ordered in 81% of cases in which it was requested clinically, with a positivity rate of 30%. Of the 34 cases in which an amyloid workup was requested (but Congo Red was not performed), 14 were positive on reevaluation. Several missed cases had deposition in multiple biopsies, and almost half were missed by subspecialist GI pathologists. Nine misinterpretations were from the stomach, with seven initially diagnosed as chemical or reactive gastropathy. Additional discrepant cases were identified from the duodenum (n = 2) and colon (n = 3), with the vascular-only deposition pattern (n = 3), muscularis mucosae-only deposition (n = 3), and globular pattern (n = 1) identified. Given the challenges of identifying amyloid on hematoxylin and eosin staining, Congo Red ordering percentage should be 100% in clinically suspicious cases unless deposition is definitively seen on hematoxylin and eosin staining.

Deep fuzzy mapping nonparametric model for real-time demand estimation in water distribution systems: A new perspective.

Hydraulic modeling has been recognized as a valuable tool for improving the design, operation, and management of water distribution systems (WDSs) as it allows engineers to simulate and analyze behaviors of WDSs in real time and help them make scientific decisions. The informatization of urban infrastructure has motivated the real-time fine-grained control of WDSs, making it one of the hotspots in recent years, thereby putting higher requirements on WDS online calibration in terms of efficiency and accuracy, especially when dealing with large-complex WDSs. To achieve this purpose, this paper proposes a novel approach (i.e., deep fuzzy mapping nonparametric model (DFM)) from a new perspective for developing a real-time WDS model. To our knowledge, this is the first work that considers uncertainties in modeling problems using fuzzy membership functions and establishes the precise inverse mapping from pressure/flow sensors to nodal water consumption for a given WDS based on the proposed DFM framework. Unlike most traditional calibration methods that require time to optimize model parameters, the DFM approach has a unique analytical solution derived through rigorous mathematical theory, thus the DFM is computationally fast as a result of sensibly handling the problems whose solutions typically require iterative numerical algorithms and large computational time. The proposed method is applied to two case studies and the results obtained show that it can produce a real-time estimation of nodal water consumption with higher accuracy, computational efficiency, and robustness relative to traditional calibration methods.

Complementary gene regulation by NRF1 and NRF2 protects against hepatic cholesterol overload.

Hepatic cholesterol overload promotes steatohepatitis. Insufficient understanding of liver stress defense impedes therapy development. Here, we elucidate the role of stress defense transcription factors, nuclear factor erythroid 2 related factor-1 (NRF1) and -2 (NRF2), in counteracting cholesterol-linked liver stress. Using a diet that increases liver cholesterol storage, expression profiles and phenotypes of liver from mice with hepatocyte deficiency of NRF1, NRF2, or both are compared with controls, and chromatin immunoprecipitation sequencing is undertaken to identify target genes. Results show NRF1 and NRF2 co-regulate genes that eliminate cholesterol and mitigate inflammation and oxidative damage. Combined deficiency, but not deficiency of either alone, results in severe steatohepatitis, hepatic cholesterol overload and crystallization, altered bile acid metabolism, and decreased biliary cholesterol. Moreover, therapeutic effects of NRF2-activating drug bardoxolone require NRF1 and are supplemented by NRF1 overexpression. Thus, we discover complementary gene programming by NRF1 and NRF2 that counteract cholesterol-associated fatty liver disease progression.

The winding road toward transcriptional repression.

Enhancers are known for their role in mediating transcriptional activation. In this issue, Vermunt et al.1 report the unexpected finding that genes can undergo a sequential transition between distinct enhancers to mediate progressive downregulation of expression.

Pathogenic human variant that dislocates GATA2 zinc fingers disrupts hematopoietic gene expression and signaling networks.

Although certain human genetic variants are conspicuously loss of function, decoding the impact of many variants is challenging. Previously, we described a patient with leukemia predisposition syndrome (GATA2 deficiency) with a germline GATA2 variant that inserts 9 amino acids between the 2 zinc fingers (9aa-Ins). Here, we conducted mechanistic analyses using genomic technologies and a genetic rescue system with Gata2 enhancer-mutant hematopoietic progenitor cells to compare how GATA2 and 9aa-Ins function genome-wide. Despite nuclear localization, 9aa-Ins was severely defective in occupying and remodeling chromatin and regulating transcription. Variation of the inter-zinc finger spacer length revealed that insertions were more deleterious to activation than repression. GATA2 deficiency generated a lineage-diverting gene expression program and a hematopoiesis-disrupting signaling network in progenitors with reduced granulocyte-macrophage colony-stimulating factor (GM-CSF) and elevated IL-6 signaling. As insufficient GM-CSF signaling caused pulmonary alveolar proteinosis and excessive IL-6 signaling promoted bone marrow failure and GATA2 deficiency patient phenotypes, these results provide insight into mechanisms underlying GATA2-linked pathologies.

Auxotrophic and prototrophic conditional genetic networks reveal the rewiring of transcription factors in Escherichia coli.

Bacterial transcription factors (TFs) are widely studied in Escherichia coli. Yet it remains unclear how individual genes in the underlying pathways of TF machinery operate together during environmental challenge. Here, we address this by applying an unbiased, quantitative synthetic genetic interaction (GI) approach to measure pairwise GIs among all TF genes in E. coli under auxotrophic (rich medium) and prototrophic (minimal medium) static growth conditions. The resulting static and differential GI networks reveal condition-dependent GIs, widespread changes among TF genes in metabolism, and new roles for uncharacterized TFs (yjdC, yneJ, ydiP) as regulators of cell division, putrescine utilization pathway, and cold shock adaptation. Pan-bacterial conservation suggests TF genes with GIs are co-conserved in evolution. Together, our results illuminate the global organization of E. coli TFs, and remodeling of genetic backup systems for TFs under environmental change, which is essential for controlling the bacterial transcriptional regulatory circuits.

Joint majorization of waterworks and secondary chlorination points considering the chloric odor and economic investment in the DWDS using machine learning and optimization algorithms.

The traditional methods of increasing the chlorine disinfectant dosage in the drinking water distribution system (DWDS) to control microorganisms and improve the safety of drinking water quality are subjected to several challenges. One noticeable problem is the unpleasant odor generated by chlorine and chloramines. However, the generally proposed chlorine dosage optimization model ignores the chloric odor distribution in the DWDS. This study proposes a comprehensive multi-parameter water quality model and aims to balance the trade-offs between: (i) minimize the flavor profile analysis (FPA) degree of the chloric odor produced by chlorine and chloramines in the DWDS, and (ii) minimize the economic investment (chlorine dosage and operation cost). EPANET and back propagation (BP) network integrated with the Borg algorithm were employed as innovative approaches to simulate the chlorine, chloramines, and chloric odor intensity in the DWDS. Moreover, the application of the multi-parameter model was demonstrated in a real-world DWDS case study. 0.5 mg-Cl2/L (mg/L) chlorine at 8 secondary chlorination points was added to the DWDS as an optimized chlorine dosing scheme considering the olfactory and financial objective functions simultaneously. When switching to a superior water source, the FPA of the chloric odor in DWDS increased by a maximum of 1.4 at most if the initial chlorine dosage remained as before. To avoid the occurrence of chloric odor and also control the residual free chlorine (residual chlorine) at a suitable value, the initial and secondary chlorine dosages were optimized to 0.4 mg/L and 0.3 mg/L, respectively. Under this condition, the initial chlorine dosage was reduced by 50% compared to the original operation scheme in City J, China, the qualification rate of the residual chlorine reached 97.2%, basically consistent with that before water source switching, and the chloric odor intensity of the DWDS was controlled below FPA 3.4.

Targeting Extracellular Cyclophilin A via an Albumin-Binding Cyclosporine A Analogue.

An albumin-binding CsA analogue 4MCsA was achieved by attachment of a thiol-reactive maleimide group at the side-chain of P4 position of CsA derivative. 4MCsA was semi-synthesized from CsA, and the cell-impermeability of albumin-4MCsA was detected by mass spectrometry and a competitive flow cytometry. 4MCsA exhibits inhibition of chemotaxis activity and inflammation by targeting extracellular CypA without immunosuppressive effect and cellular toxicity. These combined results suggested that 4MCsA can be restricted extracellularly through covalently binding to Cys34 of albumin with its maleimide group, and regulate the functions of cyclophilin A extracellularly.

NS398 as a potential drug for autosomal-dominant polycystic kidney disease: Analysis using bioinformatics, and zebrafish and mouse models.

Autosomal-dominant polycystic kidney disease (ADPKD) is characterized by uncontrolled renal cyst formation, and few treatment options are available. There are many parallels between ADPKD and clear-cell renal cell carcinoma (ccRCC); however, few studies have addressed the mechanisms linking them. In this study, we aimed to investigate their convergences and divergences based on bioinformatics and explore the potential of compounds commonly used in cancer research to be repurposed for ADPKD. We analysed gene expression datasets of ADPKD and ccRCC to identify the common and disease-specific differentially expressed genes (DEGs). We then mapped them to the Connectivity Map database to identify small molecular compounds with therapeutic potential. A total of 117 significant DEGs were identified, and enrichment analyses results revealed that they are mainly enriched in arachidonic acid metabolism, p53 signalling pathway and metabolic pathways. In addition, 127 ccRCC-specific up-regulated genes were identified as related to the survival of patients with cancer. We focused on the compound NS398 as it targeted DEGs and found that it inhibited the proliferation of Pkd1-/- and 786-0 cells. Furthermore, its administration curbed cystogenesis in Pkd2 zebrafish and early-onset Pkd1-deficient mouse models. In conclusion, NS398 is a potential therapeutic agent for ADPKD.

Foul sewer model development using geotagged information and smart water meter data.

Hydraulic modeling of a foul sewer system (FSS) enables a better understanding of the behavior of the system and its effective management. However, there is generally a lack of sufficient field measurement data for FSS model development due to the low number of in-situ sensors for data collection. To this end, this study proposes a new method to develop FSS models based on geotagged information and water consumption data from smart water meters that are readily available. Within the proposed method, each sewer manhole is firstly associated with a particular population whose size is estimated from geotagged data. Subsequently, a two-stage optimization framework is developed to identify daily time-series inflows for each manhole based on physical connections between manholes and population as well as sewer sensor observations. Finally, a new uncertainty analysis method is developed by mapping the probability distributions of water consumption captured by smart meters to the stochastic variations of wastewater discharges. Two real-world FSSs are used to demonstrate the effectiveness of the proposed method. Results show that the proposed method can significantly outperform the traditional FSS model development approach in accurately simulating the values and uncertainty ranges of FSS hydraulic variables (manhole water depths and sewer flows). The proposed method is promising due to the easy availability of geotagged information as well as water consumption data from smart water meters in near future.

Characterization of enoxacin (ENO) during ClO2 disinfection in water distribution system: Kinetics, byproducts, toxicity evaluation and halogenated disinfection byproducts (DBPs) formation potential.

Enoxacin (ENO) is widespread in water because it is commonly used as a human and veterinary antibiotic. However, little effort has been dedicated to revealing the transformation mechanisms of ENO destruction using ClO2, especially within a water distribution system (WDS). To address this knowledge gap, the kinetics, byproducts, toxicity, and formation potential of halogenated disinfection byproducts (DBPs) associated with ENO destruction using ClO2 in a pilot-scale PE pipe was explored for the first time. Statistical analyses showed that the destruction efficiency of ENO in the pilot-scale PE pipe was lower than that in deionized water (DI water), and the reactions in DI water followed the second-order kinetic model. Furthermore, pH has a significant effect on the destruction of ENO, and the removal ratio increased at a higher pH. Additionally, increasing the flow rate elevated the ENO removal efficiency; however, the influence of flow velocity was limited to ENO destruction. The ENO removal rates within the diverse pipes exhibited the following order: stainless steel pipe < PE pipe < ductile iron pipe. Nine possible intermediates were identified, and those that were formed by piperazine group cleavage represented the major primary byproducts of the entire destruction process. Additionally, the ENO destruction in a pilot-scale PE pipe had minimal influence on halogenated DBPs and chlorite formation. Finally, the toxicity evaluation illustrated that the presence of ENO increased the potential risk of water quality safety when treated with ClO2.

Semisynthesis of CRV431.

The non-immune-suppressive cyclophilin inhibitor CRV431 is a clinical candidate to cure nonalcoholic steatohepatitis (NASH) and has the potential to treat liver fibrosis and cancer incidence. Herein we report a concise chemical semisynthesis of CRV431 in four steps from the commercially available cyclosporine, featuring in this the flow-chemistry-based methylenation an intermolecular ring-closing metathesis and a Rh-catalyzed diastereoselective hydrogenation.

From fuzziness to precision medicine: on the rapidly evolving proteomics with implications in mitochondrial connectivity to rare human disease.

Mitochondrial (mt) dysfunction is linked to rare diseases (RDs) such as respiratory chain complex (RCC) deficiency, MELAS, and ARSACS. Yet, how altered mt protein networks contribute to these ailments remains understudied. In this perspective article, we identified 21 mt proteins from public repositories that associate with RCC deficiency, MELAS, or ARSACS, engaging in a relatively small number of protein-protein interactions (PPIs), underscoring the need for advanced proteomic and interactomic platforms to uncover the complete scope of mt connectivity to RDs. Accordingly, we discuss innovative untargeted label-free proteomics in identifying RD-specific mt or other macromolecular assemblies and mapping of protein networks in complex tissue, organoid, and stem cell-differentiated neurons. Furthermore, tag- and label-based proteomics, genealogical proteomics, and combinatorial affinity purification-mass spectrometry, along with advancements in detecting and integrating transient PPIs with single-cell proteomics and transcriptomics, collectively offer seminal follow-ups to enrich for RD-relevant networks, with implications in RD precision medicine.

Real-time foul sewer hydraulic modelling driven by water consumption data from water distribution systems.

Real-time hydraulic modelling can be used to address a wide range of issues in a foul sewer system and hence can help improve its daily operation and maintenance. However, the current bottleneck within real-time FSS modelling is the lack of spatio-temporal inflow data. To address the problem, this paper proposes a new method to develop real-time FSS models driven by water consumption data from associated water distribution systems (WDSs) as they often have a proportionally larger number of sensors. Within the proposed method, the relationship between FSS manholes and WDS water consumption nodes are determined based on their underlying physical connections. An optimization approach is subsequently proposed to identify the transfer factor k between nodal water consumption and FSS manhole inflows based on historical observations. These identified k values combined with the acquired real-time nodal water consumption data drive the FSS real-time modelling. The proposed method is applied to two real FSSs. The results obtained show that it can produce simulated sewer flows and manhole water depths matching well with observations at the monitoring locations. The proposed method achieved high R2, NSE and KGE (Kling-Gupta efficiency) values of 0.99, 0.88 and 0.92 respectively. It is anticipated that real-time models developed by the proposed method can be used for improved FSS management and operation.

Assessing the global resilience of water quality sensor placement strategies within water distribution systems.

Water quality sensors are often spatially distributed in water distribution systems (WDSs) to detect contamination events and monitor quality parameters (e.g., chlorine residual levels), thereby ensuring safety of a WDS. The performance of a water quality sensor placement strategy (WQSPS) is not only affected by sensor spatial deployment that has been extensively analyzed in literature, but also by possible sensor failures that have been rarely explored so far. However, enumerating all possible sensor failure scenarios is computationally infeasible for a WQSPS with a large number of sensors. To this end, this paper proposes an evolutionary algorithm (EA) based method to systematically and efficiently investigate the WQSPS' global resilience considering all likely sensor failures. First, new metrics are developed in the proposed method to assess the global resilience of a WQSPS. This is followed by a proposal of an efficient optimization approach based on an EA to identify the values of global resilience metrics. Finally, the sensors within the WQSPS are ranked to identify their relative importance in maintaining the WQSPS's detection performance. Two real-world WDSs with four WQSPSs for each case study are used to demonstrate the utility of the proposed method. Results show that: (i) compared to the traditional global resilience analysis method, the proposed EA-based approach identifies improved values of global resilience metrics, (ii) the WQSPSs that deploy sensors close to large demand users are overall more resilient in handling sensor failures relative to other design solutions, thus offering important insight to facilitate the selection of WQSPSs, and (iii) sensor rankings based on the global resilience can identify those sensors whose failure would significantly reduce the WQSPS's performance thereby providing guidance to enable effective water quality sensor management and maintenance.

Rewiring of the Human Mitochondrial Interactome during Neuronal Reprogramming Reveals Regulators of the Respirasome and Neurogenesis.

Mitochondrial protein (MP) assemblies undergo alterations during neurogenesis, a complex process vital in brain homeostasis and disease. Yet which MP assemblies remodel during differentiation remains unclear. Here, using mass spectrometry-based co-fractionation profiles and phosphoproteomics, we generated mitochondrial interaction maps of human pluripotent embryonal carcinoma stem cells and differentiated neuronal-like cells, which presented as two discrete cell populations by single-cell RNA sequencing. The resulting networks, encompassing 6,442 high-quality associations among 600 MPs, revealed widespread changes in mitochondrial interactions and site-specific phosphorylation during neuronal differentiation. By leveraging the networks, we show the orphan C20orf24 as a respirasome assembly factor whose disruption markedly reduces respiratory chain activity in patients deficient in complex IV. We also find that a heme-containing neurotrophic factor, neuron-derived neurotrophic factor [NENF], couples with Parkinson disease-related proteins to promote neurotrophic activity. Our results provide insights into the dynamic reorganization of mitochondrial networks during neuronal differentiation and highlights mechanisms for MPs in respirasome, neuronal function, and mitochondrial diseases.

A Tag-Based Affinity Purification Mass Spectrometry Workflow for Systematic Isolation of the Human Mitochondrial Protein Complexes.

Mitochondria (mt) are double-membraned, dynamic organelles that play an essential role in a large number of cellular processes, and impairments in mt function have emerged as a causative factor for a growing number of human disorders. Given that most biological functions are driven by physical associations between proteins, the first step towards understanding mt dysfunction is to map its protein-protein interaction (PPI) network in a comprehensive and systematic fashion. While mass-spectrometry (MS) based approaches possess the high sensitivity ideal for such an endeavor, it also requires stringent biochemical purification of bait proteins to avoid detecting spurious, non-specific PPIs. Here, we outline a tagging-based affinity purification coupled with mass spectrometry (AP-MS) workflow for discovering new mt protein associations and providing novel insights into their role in mt biology and human physiology/pathology. Because AP-MS relies on the creation of proteins fused with affinity tags, we employ a versatile-affinity (VA) tag, consisting of 3× FLAG, 6 × His, and Strep III epitopes. For efficient delivery of affinity-tagged open reading frames (ORF) into mammalian cells, the VA-tag is cloned onto a specific ORF using Gateway recombinant cloning, and the resulting expression vector is stably introduced in target cells using lentiviral transduction. In this chapter, we show a functional workflow for mapping the mt interactome that includes tagging, stable transduction, selection and expansion of mammalian cell lines, mt extraction, identification of interacting protein partners by AP-MS, and lastly, computational assessment of protein complexes/PPI networks.

Chlorination of enoxacin (ENO) in the drinking water distribution system: Degradation, byproducts, and toxicity.

Chlorine is widely used as a drinking water disinfectant to ensure water security. However, the transformation mechanisms of its degradation of emerging pollutants within the water distribution system (WDS) is insufficiently understood. Thus, the kinetics, degradation byproducts, and toxicity of the chlorination of enoxacin (ENO, a type of emerging pollutant) were explored in a pilot-scale WDS for the first time. It was found that the chlorination rate of ENO was higher in deionized water (DW) than in the pilot-scale WDS, and the degradation followed second-order kinetics in DW. The degradation efficiency was found to be sensitive to pH, and was highest at a pH of 7.4. The chlorination rate of ENO increased with increasing temperature in both DW and WDS. For different pipe materials, the relative performance of ENO chlorination efficiency followed the order of steel pipe > ductile iron pipe > polyethylene (PE) pipe. Seven intermediates were identified during ENO chlorination, and the primary oxidation reaction involved the cleavage of the piperazine group. Finally, it was found that the potential for chlorine toxicity in treated drinking water in the presence of ENO is higher than it is without this pollutant.

Effects of Different Alcohol Dosages on Steering Behavior in Curve Driving.

OBJECTIVE: The aim of this article is to explore the detailed characteristics of steering behavior in curve driving at different alcohol dosages. BACKGROUND: Improper operation of the steering wheel is a contributing factor to increased crash risks on curves. METHOD: The experiments were conducted using a driving simulator. Twenty-five licensed drivers were recruited to perform the experiments at the four different breath alcohol concentration (BrAC) levels. The steering angle (SA), steering speed (SS), steering reversal rate (SRR), and peak-to-peak value of the steering angle (PP) were used to characterize the steering behavior. The vehicle's speed and the number of lane exceedances per kilometer were also used to examine the driving performance. RESULTS: The SSs on the 200 m (χ2(3) = 20.67, p < .001), 500 m (χ2(3) = 22.42, p < .001), and 800 m (χ2(3) = 22.86, p < .001) radius curves were significantly faster for drivers under the influence of alcohol compared with those given a placebo. There were significant effects of alcohol on the SRR and PP on the 200 m, 500 m, and 800 m radius curves. CONCLUSION: For all of the curves, the SS, SRR, and PP had a tendency to increase as the BrAC increased. The large PP at a high BrAC, accompanied by the high speed, SS, and SRR, resulted in a high probability of lane exceedance. The use of measures of SS, SRR, and PP aided in the improvement of the accuracy of the intoxication detection for the different types of curves. APPLICATION: The most important application is to provide guidance for detecting alcohol-impaired-driving.