A non-linear partial least squares based on monotonic inner relation.

A novel regression model, monotonic inner relation-based non-linear partial least squares (MIR-PLS), is proposed to address complex issues like limited observations, multicollinearity, and nonlinearity in Chinese Medicine (CM) dose-effect relationship experimental data. MIR-PLS uses a piecewise mapping function based on monotonic cubic splines to model the non-linear inner relations between input and output score vectors. Additionally, a new weight updating strategy (WUS) is developed by leveraging the properties of monotonic functions. The proposed MIR-PLS method was compared with five well-known PLS variants: standard PLS, quadratic PLS (QPLS), error-based QPLS (EB-QPLS), neural network PLS (NNPLS), and spline PLS (SPL-PLS), using CM dose-effect relationship datasets and near-infrared (NIR) spectroscopy datasets. Experimental results demonstrate that MIR-PLS exhibits general applicability, achieving excellent predictive performances in the presence or absence of significant non-linear relationships. Furthermore, the model is not limited to CM dose-effect relationship research and can be applied to other regression tasks.

An in-depth evaluation of federated learning on biomedical natural language processing for information extraction.

Language models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP). However, the medical field faces challenges in training LMs due to limited data access and privacy constraints imposed by regulations like the Health Insurance Portability and Accountability Act (HIPPA) and the General Data Protection Regulation (GDPR). Federated learning (FL) offers a decentralized solution that enables collaborative learning while ensuring data privacy. In this study, we evaluated FL on 2 biomedical NLP tasks encompassing 8 corpora using 6 LMs. Our results show that: (1) FL models consistently outperformed models trained on individual clients' data and sometimes performed comparably with models trained with polled data; (2) with the fixed number of total data, FL models training with more clients produced inferior performance but pre-trained transformer-based models exhibited great resilience. (3) FL models significantly outperformed pre-trained LLMs with few-shot prompting.

Numerical Simulation Study on Combustion of Low Calorific Value Waste Blended with Biomass.

Numerical simulations of a 600 t/day waste incinerator was carried out using the fluid dynamic incinerator code and Fluent to evaluate the effect of biomass blending on furnace temperature, pollutant generation, and selective noncatalytic-reduction (SNCR) denitrification when treating low calorific-value waste. The results show that as the biomass blending ratio increases, the water content gradually decreases, the calorific value increases, and the maximum temperature of the incinerator gradually increases from 1227 to 1408 K, while the content of exported NOx increases from 579 to 793 mg/Nm3; during the combustion of low-quality waste, the residence time of the flue gas in the high-temperature region (above 1123 K) is 1.62 s. When the biomass blending ratio exceeds 20%, the residence time of the flue gas in the high-temperature region is more than 2 s, which can effectively curb the generation of dioxin. When the biomass blending ratio is 20%, and the normalized stoichiometric ratio (2nurea/nNO) of urea injected into the SNCR is 1.1, the NOx concentration at the outlet is 230.08 mg/Nm3, which satisfies the NOx emission standard of less than 250 mg/Nm3.

Distinct developmental reprogramming footprint of macrophages during acute kidney injury across species.

Acute kidney injury (AKI) is a common finding in hospitalized patients, particularly those who are critically ill. The development of AKI is associated with several adverse outcomes including mortality, morbidity, progression to chronic kidney disease, and an increase in healthcare expenditure. Despite the well-established negative impact of AKI and rigorous efforts to better define, identify, and implement targeted therapies, the overall approach to the treatment of AKI continues to principally encompass supportive measures. This enduring challenge is primarily due to the heterogeneous nature of insults that activate many independent and overlapping molecular pathways. Consequently, it is evident that the identification of common mechanisms that mediate the pathogenesis of AKI, independent of etiology and engaged pathophysiological pathways, is of paramount importance and could lead to the identification of novel therapeutic targets. To better distinguish the commonly modulated mechanisms of AKI, we explored the transcriptional characteristics of human kidney biopsies from patients with acute tubular necrosis (ATN), and acute interstitial nephritis (AIN) using a NanoString inflammation panel. Subsequently, we used publicly available single-cell transcriptional resources to better interpret the generated transcriptional findings. Our findings identify robust acute kidney injury (AKI-induced) developmental reprogramming of macrophages (MΦ) with the expansion of C1Q+, CD163+ MΦ that is independent of the etiology of AKI and conserved across mouse and human species. These results would expand the current understanding of the pathophysiology of AKI and potentially offer novel targets for additional studies to enhance the translational transition of AKI research.NEW & NOTEWORTHY Our findings identify robust acute kidney injury (AKI)-induced developmental reprogramming of macrophages (MΦ) with the expansion of C1Q+, CD163+ MΦ that is independent of the etiology of AKI and conserved across mouse and human species.

An improved particle swarm optimization combined with double-chaos search.

Particle swarm optimization (PSO) has been successfully applied to various complex optimization problems due to its simplicity and efficiency. However, the update strategy of the standard PSO algorithm is to learn from the global best particle, making it difficult to maintain diversity in the population and prone to premature convergence due to being trapped in local optima. Chaos search mechanism is an optimization technique based on chaotic dynamics, which utilizes the randomness and nonlinearity of a chaotic system for global search and can escape from local optima. To overcome the limitations of PSO, an improved particle swarm optimization combined with double-chaos search (DCS-PSO) is proposed in this paper. In DCS-PSO, we first introduce double-chaos search mechanism to narrow the search space, which enables PSO to focus on the neighborhood of the optimal solution and reduces the probability that the swarm gets trapped into a local optimum. Second, to enhance the population diversity, the logistic map is employed to perform a global search in the narrowed search space and the best solution found by both the logistic and population search guides the population to converge. Experimental results show that DCS-PSO can effectively narrow the search space and has better convergence accuracy and speed in most cases.

An acetyltranferase moonlights as a regulator of the RNA binding repertoire of the RNA chaperone Hfq in Escherichia coli.

Bacterial small RNAs (sRNAs) regulate gene expression by base-pairing with their target mRNAs. In Escherichia coli and many other bacteria, this process is dependent on the RNA chaperone Hfq, a mediator for sRNA-mRNA annealing. YhbS (renamed here as HqbA), a putative Gcn5-related N-acetyltransferase (GNAT), was previously identified as a silencer of sRNA signaling in a genomic library screen. Here, we studied how HqbA regulates sRNA signaling and investigated its physiological roles in modulating Hfq activity. Using fluorescent reporter assays, we found that HqbA overproduction suppressed all tested Hfq-dependent sRNA signaling. Direct interaction between HqbA and Hfq was demonstrated both in vivo and in vitro, and mutants that blocked the interaction interfered with HqbA suppression of Hfq. However, an acetylation-deficient HqbA mutant still disrupted sRNA signaling, and HqbA interacted with Hfq at a site far from the active site. This suggests that HqbA may be bifunctional, with separate roles for regulating via Hfq interaction and for acetylation of undefined substrates. Gel shift assays revealed that HqbA strongly reduced the interaction between the Hfq distal face and low-affinity RNAs but not high-affinity RNAs. Comparative RNA immunoprecipitation of Hfq and sequencing showed enrichment of two tRNA precursors, metZWV and proM, by Hfq in mutants that lost the HqbA-Hfq interaction. Our results suggest that HqbA provides a level of quality control for Hfq by competing with low-affinity RNA binders.

Accuracy assessment of land cover products in China from 2000 to 2020.

The accuracy assessment of land cover data is of significant value to accurately monitor and objectively reproduce spatio-temporal dynamic changes to land surface landscapes. In this study, the interpretation and applicability of CCI, MCD, and CGLS long time-series land cover data products for China were evaluated via consistency analysis and a confusion matrix system using NLUD-C periodic products as reference data. The results showed that CGLS had the highest overall accuracy, Kappa coefficient, and area consistency in the continuous time-series evaluation, followed by MCD, whereas CCI had the worst performance. For the accuracy assessment of subdivided land cover types, the three products could accurately describe the distribution of forest land in China with a high recognition level, but their recognition ability for water body and construction land was poor. Among the other types, CCI could better identify cropland, MCD for grassland, and CGLS for unused land. Based on these evaluation results and characteristics of the data products, we developed suitable selection schemes for users with different requirements.

The association between the thyroid feedback quantile-based index and serum uric acid in U.S. adults.

OBJECTIVES: Previous studies have shown that there may be a positive correlation between serum uric acid levels and hyperthyroidism. However, the relationship between thyroid function and serum uric acid in healthy people is unclear. This study analyzed the relationship between impaired thyroid hormone sensitivity and serum uric acid levels, and presented them in quantitative form. RESEARCH DESIGN AND METHODS: This is a cross-sectional study of 4460 adults (male: 2300; female: 2160) who participated in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2010. Parameters representing central sensitivity to thyroid hormones were calculated as: thyroid feedback quantile-based index (TFQIFT4), thyroid stimulating hormone index (TSHI), and total thyroxine (T4) resistance index (TT4RI); Peripheral sensitivity to thyroid hormone was evaluated by FT3/FT4 ratio. In addition, we have innovated total triiodothyronine (T3) resistance index (TT3RI) and TFQIFT3 indexes based on FT3 and TSH. Multiple linear regression models were used to evaluate the correlation between thyroid resistance index and serum uric acid, and the results were presented graphically as smooth curve fittings. RESULTS: Higher levels of serum uric acid were associated with decreased sensitivity to thyroid hormones in euthyroid individuals. In conjunction with an increase in the thyroid hormone sensitivity index value, uric acid levels gradually increased as well. Furthermore, we found a segmented relationship between TT3RI and serum uric acid changes. The saturation and threshold analyses indicated that 18.85 was the turning point (logarithmic likelihood ratio test = 0.036). When TT3RI < 18.85, the relationship between serum uric acid and TT3RI was not significant [ß(95% CI) 0.47 (- 0.05, 1.00), P = 0.077], but when TT3RI > 18.85, there was a significant rise in serum uric acid with an increase in TT3RI [ß(95% CI) 3.94 (0.94, 6.95), P = 0.010]. A further finding of the interaction test was that impaired thyroid hormone sensitivity and uric acid changes vary among different age groups and BMI levels. CONCLUSIONS: Decreased sensitivity to thyroid hormones was associated with high levels of serum uric acid in people with normal thyroid function. The interaction test shows that different age groups and BMI groups impact the association between impaired thyroid hormone sensitivity and serum uric acid. Furthermore, smooth curve fitting revealed a segmental relationship between TT3RI and serum uric acid levels.

Bacteria and poisonous plants/fungi were the primary causative hazards of foodborne disease outbreaks: A five-year survey from Guangzhou, Guangdong.

The burden of foodborne diseases is of serious concern. More effective and localized intervention policies for outbreak prevention and management are required; however, policy modification is hampered due to a lack of information on the epidemiological characteristics of outbreaks in Guangzhou. We collected data from 182 foodborne disease outbreaks reported in Guangzhou, China from 2017 to 2021 to investigate the epidemiological characteristics and associated factors. Nine outbreaks were serious enough to be labelled as level IV public health emergencies, all of which were associated with canteens. In terms of the number of outbreaks, morbidity and clinical medical needs, bacteria and poisonous plants/fungi were the primary causative hazards of outbreaks, and were found mostly in foodservice establishments (96 %, 95/99) and private homes (86 %, 37/43) respectively. Surprisingly, Vibrio parahaemolyticus was primarily identified in meat and poultry products rather than in aquatic products in these outbreaks. Patient specimens and food samples were among the most common sources of detected pathogens in foodservice establishments and private homes. Cross-contamination (35 %), improper processing (32 %) and equipment/utensil contamination (30 %) were the top three risk factors for outbreaks related to foodservice establishments, while accidental ingestion of poisonous food (78 %) was the most common risk factor in private homes. Based on the above epidemiological characteristics of the outbreaks, key foodborne disease intervention policy points should be to raise public awareness of harmful food and avoid risk behaviour, improve handler hygiene training, and strengthen the hygiene management and supervision of kitchens, especially canteens in collective units.

Xinkeshu for coronary heart disease complicated with anxiety or depression: A meta-analysis of randomized controlled trials.

ETHNOPHARMACOLOGICAL RELEVANCE: The incidence of coronary heart disease (CHD) complicated with anxiety or depression is increasing year by year. However, many anti-anxiety drugs or antidepressants have a certain degree of adverse reactions and are not easily accepted by patients. Xinkeshu (XKS), as a proprietary Chinese patent medicine with "psycho-cardiology" effect, is one of the commonly used drugs in the treatment of CHD complicated with anxiety or depression in China. AIM OF THE STUDY: To systematically evaluate the efficacy and safety of XKS for CHD complicated with anxiety or depression. METHODS: Nine different electronic databases were independently searched to include randomized controlled trials (RCTs) of XKS for CHD complicated with anxiety or depression published from inception to February 2022, and the methodological quality was evaluated using the bias risk assessment tool from Cochrane Handbook 5.0 and the modified Jadad scale. Meta-analysis was performed using RevMan 5.3 and Stata 16.0 software. The GRADE Profiler 3.6.1 and TSA 0.9.5.10 beta were adopted to evaluate the certainty and conclusiveness of the evidence. RESULTS: A total of 18 RCTs involving 1907 subjects were included. There were 956 subjects in the XKS group and 951 subjects in the control group. Baseline conditions were consistent and comparable between the groups. Compared with single-use western medicine (WM), XKS combined with WM significantly reduced scores of Hamilton Anxiety Scale (HAMA) [Mean difference (MD) = -7.60, 95% confidence interval (95% CI) (-10.37, -4.83), P < 0.000 01], Zung Self-rating Anxiety Scale (SAS) [MD = -10.05, 95% CI (-12.70, -7.41), P < 0.000 01], Hamilton Depression Scale (HAMD) [MD = -6.74, 95% CI (-11.58, -1.90), P = 0.006], and Zung Self-rating Depression Scale (SDS) [MD = -10.75, 95% CI (-17.05,-4.45), P = 0.000 8], as well as improved clinical effective rate [odds ratio (OR) = 4.24, 95% CI (2.47, 7.27), P < 0.000 01]. In terms of safety, 4 studies reported the adverse reactions in detail. The severity was mild and symptoms disappeared after treatment. CONCLUSION: Current evidence indicates that XKS may be effective and safe in the treatment of patients with CHD complicated with anxiety or depression. Since the quality of the literature included in this study was generally low, there is an urgent need for more RCTs with high quality, low bias risk and sufficient sample size to validate our conclusions.

Phase Change Composite Microcapsules with Low-Dimensional Thermally Conductive Nanofillers: Preparation, Performance, and Applications.

Phase change materials (PCMs) have been extensively utilized in latent thermal energy storage (TES) and thermal management systems to bridge the gap between thermal energy supply and demand in time and space, which have received unprecedented attention in the past few years. To effectively address the undesirable inherent defects of pristine PCMs such as leakage, low thermal conductivity, supercooling, and corrosion, enormous efforts have been dedicated to developing various advanced microencapsulated PCMs (MEPCMs). In particular, the low-dimensional thermally conductive nanofillers with tailorable properties promise numerous opportunities for the preparation of high-performance MEPCMs. In this review, recent advances in this field are systematically summarized to deliver the readers a comprehensive understanding of the significant influence of low-dimensional nanofillers on the properties of various MEPCMs and thus provide meaningful enlightenment for the rational design and multifunction of advanced MEPCMs. The composition and preparation strategies of MEPCMs as well as their thermal management applications are also discussed. Finally, the future perspectives and challenges of low-dimensional thermally conductive nanofillers for constructing high performance MEPCMs are outlined.

Sensitivity and Uncertainty Analysis for Two-stream Capture-Recapture Methods in Disease Surveillance.

Capture-recapture methods are widely applied in estimating the number ( ) of prevalent or cumulatively incident cases in disease surveillance. Here, we focus the bulk of our attention on the common case in which there are 2 data streams. We propose a sensitivity and uncertainty analysis framework grounded in multinomial distribution-based maximum likelihood, hinging on a key dependence parameter that is typically nonidentifiable but is epidemiologically interpretable. Focusing on the epidemiologically meaningful parameter unlocks appealing data visualizations for sensitivity analysis and provides an intuitively accessible framework for uncertainty analysis designed to leverage the practicing epidemiologist's understanding of the implementation of the surveillance streams as the basis for assumptions driving estimation of . By illustrating the proposed sensitivity analysis using publicly available HIV surveillance data, we emphasize both the need to admit the lack of information in the observed data and the appeal of incorporating expert opinion about the key dependence parameter. The proposed uncertainty analysis is a simulation-based approach designed to more realistically acknowledge variability in the estimated associated with uncertainty in an expert's opinion about the nonidentifiable parameter, together with the statistical uncertainty. We demonstrate how such an approach can also facilitate an appealing general interval estimation procedure to accompany capture-recapture methods. Simulation studies illustrate the reliable performance of the proposed approach for quantifying uncertainties in estimating in various contexts. Finally, we demonstrate how the recommended paradigm has the potential to be directly extended for application to data from >2 surveillance streams.

Potential benefits of public-private partnerships to improve the efficiency of urban wastewater treatment.

For emerging economies lacking public budgets, continuous improvement of urban wastewater treatment efficiency (UWTE) requires effective government supervision of wastewater treatment infrastructures (WTIs) and participation of private capital seeking to profit-maximising. However, to what extent this public-private partnership (PPP) model, aimed at a reasonable sharing of benefit and risk, in delivering WTIs can improve the UWTE is unknown. We evaluated the impact of the PPP model on the UWTE by collecting data from 1303 urban wastewater treatment PPP projects in 283 prefecture-level cities in China from 2014 to 2019 and used data envelopment analysis and Tobit regression model. The UWTE was significantly higher in prefecture-level cities that introduced the PPP model in the construction and operation of WTIs, particularly those with a feasibility gap subsidy, competitive procurement, privatised operation, and non-demonstration. Moreover, the effects of PPPs on UWTE were limited by the economic development level, marketisation, and climatic conditions.

Effects of pair housing on behavior, cortisol, and clinical outcomes during quarantine-like procedures for rhesus macaques (Macaca mulatta).

BACKGROUND: Compatible pair housing of macaques in research settings increases species-typical behaviors and facilitates beneficial social buffering. It is not yet established whether these benefits are maintained after intrafacility transfer and domestic quarantine, which are two stressors that can lead to behavioral and clinical abnormalities. METHODS: We evaluated 40 adolescent male rhesus macaques who were single- or pair-housed immediately following an intrafacility transfer. We measured behavior, fecal cortisol, body weight, and diarrhea occurrence. Body weight and diarrhea occurrence were also retrospectively analyzed in an additional 120 adolescent rhesus who underwent a similar transfer. RESULTS AND CONCLUSIONS: Pair-housed macaques exhibited less of some undesirable behaviors (e.g., self-clasping) and experienced less diarrhea than single-housed subjects; however, no significant differences in cortisol levels or alopecia measures were found. The demonstrated beneficial effects of pair housing for rhesus macaques following intrafacility transfer and adjustment suggest pairing upon arrival at a new facility will bolster animal welfare.

Spatio-temporal efficiency of fiscal environmental expenditure in reducing CO2 emissions in China's cities.

Although market-based CO2 emission control measures (e.g., carbon tax and carbon trading market) have been deeply discussed, government-based measures have received limited attention. This has led to increased uncertainty regarding the formulation of targeted emission reduction policies. Using a unique dataset, the non-radial directional distance function, a proposed spatial meta-frontier analysis method, and the log t convergence model, this study comprehensively investigates the spatio-temporal trends in fiscal environmental expenditure efficiency (FE) and corresponding causes for in a case study for 106 Chinese cities over 2007-2019. The results show that city-level FE presented a slow upward trend at a relatively low level, with a clearly skewed distribution. The technology gap effect between city groups and the overall best production technology, and the efficiency gap effect within city groups were the main drivers widening the overall FE gap. Convergence analysis indicated that three convergence clubs of FE were found, which were distributed across the country. This study highlights that, when constructing fiscal environmental expenditure policies, the government should focus on balancing the regional gap of FE while comprehensively improving FE.

Feature selection based on neighborhood rough sets and Gini index.

Neighborhood rough set is considered an essential approach for dealing with incomplete data and inexact knowledge representation, and it has been widely applied in feature selection. The Gini index is an indicator used to evaluate the impurity of a dataset and is also commonly employed to measure the importance of features in feature selection. This article proposes a novel feature selection methodology based on these two concepts. In this methodology, we present the neighborhood Gini index and the neighborhood class Gini index and then extensively discuss their properties and relationships with attributes. Subsequently, two forward greedy feature selection algorithms are developed using these two metrics as a foundation. Finally, to comprehensively evaluate the performance of the algorithm proposed in this article, comparative experiments were conducted on 16 UCI datasets from various domains, including industry, food, medicine, and pharmacology, against four classical neighborhood rough set-based feature selection algorithms. The experimental results indicate that the proposed algorithm improves the average classification accuracy on the 16 datasets by over 6%, with improvements exceeding 10% in five. Furthermore, statistical tests reveal no significant differences between the proposed algorithm and the four classical neighborhood rough set-based feature selection algorithms. However, the proposed algorithm demonstrates high stability, eliminating most redundant or irrelevant features effectively while enhancing classification accuracy. In summary, the algorithm proposed in this article outperforms classical neighborhood rough set-based feature selection algorithms.

Plasma S-Klotho level affects the risk of hyperuricemia in the middle-aged and elderly people.

BACKGROUND: Soluble Klotho (S-Klotho) is an anti-aging protein mainly secreted by the kidneys. Hyperuricemia is prevalent among middle-aged and elderly individuals, which affects the development of various chronic diseases. However, there are relatively few studies investigating the association between plasma S-Klotho levels and hyperuricemia in middle-aged and elderly individuals. This study sought to clarify the relationship between S-Klotho and the risk of hyperuricemia in middle-aged and elderly people. METHODS: During 2007-2016, a total of 50,588 people participated in the National Health and Nutrition Examination Survey. Finally, 12,441 middle-aged and elderly people (aged 40-79) completed the soluble Klotho tests and had obtained complete data. S-Klotho was detected by ELISA kit, and the relationship between S-Klotho and hyperuricemia was assessed by multiple logistic regression. Hyperuricemia is defined as serum uric acid levels higher than or equal to 420 mmol/l in men and 360 mmol/l in women. RESULTS: In the middle-aged and elderly, plasma S-Klotho levels were negatively correlated with hyperuricemia, and there was a saturation effect. The inflection point of S-Klotho was 927.8 pg/ml (logarithmic likelihood ratio test = 0.002). When plasma S-Klotho < 927.8 pg/ml, the prevalence of hyperuricemia in middle-aged and elderly individuals with higher levels of S-Klotho decreased by 25.6% compared with those with low levels of S-Klotho [Q4 vs Q1, OR: 0.744, 95%CI: (0.634, 0.874), P < 0.001]; In different age groups, S-Klotho had a significantly greater effect on hyperuricemia in middle-aged people [age: 40-65 years, Q4 vs Q1, OR (95%CI): 0.69 (0.58, 0.82), P < 0.001; Age > 65 years: Q4 vs Q1, OR (95%CI): 0.72 (0.56, 0.92), P = 0.008)].When the level of S-Klotho was higher, the risk of hyperuricemia in men was lower than that in women [male: Q4 vs Q1, OR (95%CI): 0.67 (0.56, 0.81), P < 0.001; female: Q4 vs Q1 (95%CI):0.72 (0.58, 0.88), P < 0.001]. CONCLUSIONS: In middle-aged and elderly individuals, plasma S-Klotho levels were inversely correlated with hyperuricemia, with a saturation effect. Given the limitations of the research results, the underlying mechanism between S-Klotho and hyperuricemia should be further explored.

Recent computational drug repositioning strategies against SARS-CoV-2.

Since COVID-19 emerged in 2019, significant levels of suffering and disruption have been caused on a global scale. Although vaccines have become widely used, the virus has shown its potential for evading immunities or acquiring other novel characteristics. Whether current drug treatments are still effective for people infected with Omicron remains unclear. Due to the long development cycles and high expense requirements of de novo drug development, many researchers have turned to consider drug repositioning in the search to find effective treatments for COVID-19. Here, we review such drug repositioning and combination efforts towards providing better handling. For potential drugs under consideration, aspects of both structure and function require attention, with specific categories of sequence, expression, structure, and interaction, the key parameters for investigation. For different data types, we show the corresponding differing drug repositioning methods that have been exploited. As incorporating drug combinations can increase therapeutic efficacy and reduce toxicity, we also review computational strategies to reveal drug combination potential. Taken together, we found that graph theory and neural network were the most used strategy with high potential towards drug repositioning for COVID-19. Integrating different levels of data may further improve the success rate of drug repositioning.

The MDMX Acidic Domain Uses Allovalency to Bind Both p53 and MDMX.

Autoinhibition of p53 binding to MDMX requires two short-linear motifs (SLiMs) containing adjacent tryptophan (WW) and tryptophan-phenylalanine (WF) residues. NMR spectroscopy was used to show the WW and WF motifs directly compete for the p53 binding site on MDMX and circular dichroism spectroscopy was used to show the WW motif becomes helical when it is bound to the p53 binding domain (p53BD) of MDMX. Binding studies using isothermal titration calorimetry showed the WW motif is a stronger inhibitor of p53 binding than the WF motif when they are both tethered to p53BD by the natural disordered linker. We also investigated how the WW and WF motifs interact with the DNA binding domain (DBD) of p53. Both motifs bind independently to similar sites on DBD that overlap the DNA binding site. Taken together our work defines a model for complex formation between MDMX and p53 where a pair of disordered SLiMs bind overlapping sites on both proteins.

S-Nitrosylation of the virulence regulator AphB promotes Vibrio cholerae pathogenesis.

Vibrio cholerae is the etiologic agent of the severe human diarrheal disease cholera. To colonize mammalian hosts, this pathogen must defend against host-derived toxic compounds, such as nitric oxide (NO) and NO-derived reactive nitrogen species (RNS). RNS can covalently add an NO group to a reactive cysteine thiol on target proteins, a process called protein S-nitrosylation, which may affect bacterial stress responses. To better understand how V. cholerae regulates nitrosative stress responses, we profiled V. cholerae protein S-nitrosylation during RNS exposure. We identified an S-nitrosylation of cysteine 235 of AphB, a LysR-family transcription regulator that activates the expression of tcpP, which activates downstream virulence genes. Previous studies show that AphB C235 is sensitive to O2 and reactive oxygen species (ROS). Under microaerobic conditions, AphB formed dimer and directly repressed transcription of hmpA, encoding a flavohemoglobin that is important for NO resistance of V. cholerae. We found that tight regulation of hmpA by AphB under low nitrosative stress was important for V. cholerae optimal growth. In the presence of NO, S-nitrosylation of AphB abolished AphB activity, therefore relieved hmpA expression. Indeed, non-modifiable aphBC235S mutants were sensitive to RNS in vitro and drastically reduced colonization of the RNS-rich mouse small intestine. Finally, AphB S-nitrosylation also decreased virulence gene expression via debilitation of tcpP activation, and this regulation was also important for V. cholerae RNS resistance in vitro and in the gut. These results suggest that the modulation of the activity of virulence gene activator AphB via NO-dependent protein S-nitrosylation is critical for V. cholerae RNS resistance and colonization.