Regulation of chlamydial spreading from the small intestine to the large intestine by IL-22-producing CD4+ T cells.

Following an oral inoculation, Chlamydia muridarum descends to the mouse large intestine for long-lasting colonization. However, a mutant C. muridarum that lacks the plasmid-encoded protein pGP3 due to an engineered premature stop codon (designated as CMpGP3S) failed to do so even following an intrajejunal inoculation. This was because a CD4+ T cell-dependent immunity prevented the spread of CMpGP3S from the small intestine to the large intestine. In the current study, we found that mice deficient in IL-22 (IL-22-/-) allowed CMpGP3S to spread from the small intestine to the large intestine on day 3 after intrajejunal inoculation, indicating a critical role of IL-22 in regulating the chlamydial spread. The responsible IL-22 is produced by CD4+ T cells since IL-22-/- mice were rescued to block the CMpGP3S spread by donor CD4+ T cells from C57BL/6J mice. Consistently, CD4+ T cells lacking IL-22 failed to block the spread of CMpGP3S in Rag2-/- mice, while IL-22-competent CD4+ T cells did block. Furthermore, mice deficient in cathelicidin-related antimicrobial peptide (CRAMP) permitted the CMpGP3S spread, but donor CD4+ T cells from CRAMP-/- mice were still sufficient for preventing the CMpGP3S spread in Rag2-/- mice, indicating a critical role of CRAMP in regulating chlamydial spreading, and the responsible CRAMP is not produced by CD4+ T cells. Thus, the IL-22-producing CD4+ T cell-dependent regulation of chlamydial spreading correlated with CRAMP produced by non-CD4+ T cells. These findings provide a platform for further characterizing the subset(s) of CD4+ T cells responsible for regulating bacterial spreading in the intestine.

Network Spreading from Network Dimension.

Continuous-state network spreading models provide critical numerical and analytic insights into transmission processes in epidemiology, rumor propagation, knowledge dissemination, and many other areas. Most of these models reflect only local features such as adjacency, degree, and transitivity, so can exhibit substantial error in the presence of global correlations typical of empirical networks. Here, we propose mitigating this limitation via a network property ideally suited to capturing spreading. This is the network correlation dimension, which characterizes how the number of nodes within range of a source typically scales with distance. Applying the approach to susceptible-infected-recovered processes leads to a spreading model which, for a wide range of networks and epidemic parameters, can provide more accurate predictions of the early stages of a spreading process than important established models of substantially higher complexity. In addition, the proposed model leads to a basic reproduction number that provides information about the final state not available from popular established models.

Distinguishing between aldosterone-producing adenomas and non-functional adrenocortical adenomas using the YOLOv5 network.

BACKGROUND: You Only Look Once version 5 (YOLOv5), a one-stage deep-learning (DL) algorithm for object detection and classification, offers high speed and accuracy for identifying targets. PURPOSE: To investigate the feasibility of using the YOLOv5 algorithm to non-invasively distinguish between aldosterone-producing adenomas (APAs) and non-functional adrenocortical adenomas (NF-ACAs) on computed tomography (CT) images. MATERIAL AND METHODS: A total of 235 patients who were diagnosed with ACAs between January 2011 and July 2022 were included in this study. Of the 215 patients, 81 (37.7%) had APAs and 134 (62.3%) had NF-ACAs' they were randomly divided into either the training set or the validation set at a ratio of 9:1. Another 20 patients, including 8 (40.0%) with APA and 12 (60.0%) with NF-ACA, were collected for the testing set. Five submodels (YOLOv5n, YOLOv5s, YOLOv5m, YOLOv5l, and YOLOv5x) of YOLOv5 were trained and evaluated on the datasets. RESULTS: In the testing set, the mAP_0.5 value for YOLOv5x (0.988) was higher than the values for YOLOv5n (0.969), YOLOv5s (0.965), YOLOv5m (0.974), and YOLOv5l (0.983). The mAP_0.5:0.95 value for YOLOv5x (0.711) was also higher than the values for YOLOv5n (0.587), YOLOv5s (0.674), YOLOv5m (0.671), and YOLOv5l (0.698) in the testing set. The inference speed of YOLOv5n was 2.4 ms in the testing set, which was the fastest among the five submodels. CONCLUSION: The YOLOv5 algorithm can accurately and efficiently distinguish between APAs and NF-ACAs on CT images, especially YOLOv5x has the best identification performance.

Collective behaviors of animal groups may stem from visual lateralization-Tending to obtain information through one eye.

Animal groups exhibit various captivating movement patterns, which manifest as intricate interactions among group members. Several models have been proposed to elucidate collective behaviors in animal groups. These models achieve a certain degree of efficacy; however, inconsistent experimental findings suggest insufficient accuracy. Experiments have shown that some organisms employ a single information channel and visual lateralization to glean knowledge from other individuals in collective movements. In this study, we consider individuals' visual lateralization and a single information channel and develop a self-propelled particle model to describe the collective behavior of large groups. The results suggest that homogeneous visual lateralization gives the group a strong sense of cohesiveness, thereby enabling diverse collective behaviors. As the overlapping field grows, the cohesiveness gradually dissipates. Inconsistent visual lateralization among group members can reduce the cohesiveness of the group, and when there is a high degree of heterogeneity in visual lateralization, the group loses their cohesiveness. This study also examines the influence of visual lateralization heterogeneity on specific formations, and the results indicate that the directional migration formation is responsive to such heterogeneity. We propose an information network to portray the transmission of information within groups, which explains the cohesiveness of groups and the sensitivity of the directional migration formation.

Estimation of Carleman operator from a univariate time series.

Reconstructing a nonlinear dynamical system from empirical time series is a fundamental task in data-driven analysis. One of the main challenges is the existence of hidden variables; we only have records for some variables, and those for hidden variables are unavailable. In this work, the techniques for Carleman linearization, phase-space embedding, and dynamic mode decomposition are integrated to rebuild an optimal dynamical system from time series for one specific variable. Using the Takens theorem, the embedding dimension is determined, which is adopted as the dynamical system's dimension. The Carleman linearization is then used to transform this finite nonlinear system into an infinite linear system, which is further truncated into a finite linear system using the dynamic mode decomposition technique. We illustrate the performance of this integrated technique using data generated by the well-known Lorenz model, the Duffing oscillator, and empirical records of electrocardiogram, electroencephalogram, and measles outbreaks. The results show that this solution accurately estimates the operators of the nonlinear dynamical systems. This work provides a new data-driven method to estimate the Carleman operator of nonlinear dynamical systems.

Metabolism, Disposition, Excretion, and Potential Transporter Inhibition of 7-16, an Improving 5-HT2A Receptor Antagonist and Inverse Agonist for Parkinson's Disease.

Compound 7-16 was designed and synthesized in our previous study and was identified as a more potential selective 5-HT2A receptor antagonist and inverse agonist for treating Parkinson's disease psychosis (PDP). Then, the metabolism, disposition, and excretion properties of 7-16 and its potential inhibition on transporters were investigated in this study to highlight advancements in the understanding of its therapeutic mechanisms. The results indicate that a total of 10 metabolites of 7-16/[14C]7-16 were identified and determined in five species of liver microsomes and in rats using UPLC-Q Exactive high-resolution mass spectrometry combined with radioanalysis. Metabolites formed in human liver microsomes could be covered by animal species. 7-16 is mainly metabolized through mono-oxidation (M470-2) and N-demethylation (M440), and the CYP3A4 isozyme was responsible for both metabolic reactions. Based on the excretion data in bile and urine, the absorption rate of 7-16 was at least 74.7%. 7-16 had weak inhibition on P-glycoprotein and no effect on the transport activity of OATP1B1, OATP1B3, OAT1, OAT3, and OCT2 transporters. The comprehensive pharmacokinetic properties indicate that 7-16 deserves further development as a new treatment drug for PDP.

Weighted Signed Networks Reveal Interactions between US Foreign Exchange Rates.

Correlations between exchange rates are valuable for illuminating the dynamics of international trade and the financial dynamics of countries. This paper explores the changing interactions of the US foreign exchange market based on detrended cross-correlation analysis. First, we propose an objective way to choose a time scale parameter appropriate for comparing different samples by maximizing the summed magnitude of all DCCA coefficients. We then build weighted signed networks under this optimized time scale, which can clearly display the complex relationships between different exchange rates. Our study shows negative cross-correlations have become pyramidally rare in the past three decades. Both the number and strength of positive cross-correlations have grown, paralleling the increase in global interconnectivity. The balanced strong triads are identified subsequently after the network centrality analysis. Generally, while the strong development links revealed by foreign exchange have begun to spread to Asia since 2010, Europe is still the center of world finance, with the euro and Danish krone consistently maintaining the closest balanced development relationship. Finally, we propose a fluctuation propagation algorithm to investigate the propagation pattern of fluctuations in the inferred exchange rate networks. The results show that, over time, fluctuation propagation patterns have become simpler and more predictable.

Novel role for epalrestat: protecting against NLRP3 inflammasome-driven NASH by targeting aldose reductase.

BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a progressive and inflammatory subtype of nonalcoholic fatty liver disease (NAFLD) characterized by hepatocellular injury, inflammation, and fibrosis in various stages. More than 20% of patients with NASH will progress to cirrhosis. Currently, there is a lack of clinically effective drugs for treating NASH, as improving liver histology in NASH is difficult to achieve and maintain through weight loss alone. Hence, the present study aimed to investigate potential therapeutic drugs for NASH. METHODS: BMDMs and THP1 cells were used to construct an inflammasome activation model, and then we evaluated the effect of epalrestat on the NLRP3 inflammasome activation. Western blot, real-time qPCR, flow cytometry, and ELISA were used to evaluate the mechanism of epalrestat on NLRP3 inflammasome activation. Next, MCD-induced NASH models were used to evaluate the therapeutic effects of epalrestat in vivo. In addition, to evaluate the safety of epalrestat in vivo, mice were gavaged with epalrestat daily for 14 days. RESULTS: Epalrestat, a clinically effective and safe drug, inhibits NLRP3 inflammasome activation by acting upstream of caspase-1 and inducing ASC oligomerization. Importantly, epalrestat exerts its inhibitory effect on NLRP3 inflammasome activation by inhibiting the activation of aldose reductase. Further investigation revealed that the administration of epalrestat inhibited NLRP3 inflammasome activation in vivo, alleviating liver inflammation and improving NASH pathology. CONCLUSIONS: Our study indicated that epalrestat, an aldose reductase inhibitor, effectively suppressed NLRP3 inflammasome activation in vivo and in vitro and might be a new therapeutic approach for NASH.

Lymph Node Posterior to the Right Recurrent Laryngeal Nerve Metastasis in Right Lobe T1a Papillary Thyroid Carcinoma: A Retrospective Cohort Study.

INTRODUCTION AND OBJECTIVES: This study analyzed the incidence and predictors of lymph node posterior to the right recurrent laryngeal nerve metastasis in T1a papillary thyroid carcinoma of the right lobe. METHODS: This was a retrospective cohort study. Patients were selected from those who had received surgical treatment for primary papillary thyroid carcinoma between January 2019 and December 2020. The association between clinicopathologic variables and lymph node posterior to the right recurrent laryngeal nerve metastasis was assessed using univariate and multivariate analyses. Postoperative complications were also described. RESULTS: Lymph node posterior to the right recurrent laryngeal nerve metastasis was present in 6.0% of the 402 study patients. It was the most likely to occur when there were other lymph node metastases, particularly in the lymph node anterior to the recurrent laryngeal nerve. Independent predictors for lymph node posterior to the right recurrent laryngeal nerve metastasis were a tumor size of ≥5.0 mm, a lower pole location, and lymph node anterior to the right recurrent laryngeal nerve metastasis. The rate of persistent vocal cord paralysis was .5%, and no patient developed permanent hypoparathyroidism. CONCLUSIONS: Although lymph node posterior to the right recurrent laryngeal nerve metastases of the right lobe T1a papillary thyroid carcinoma is uncommon, the possibility of metastasis should be investigated when there is a positive lymph node anterior to the right recurrent laryngeal nerve in a tumor >5.0 mm in size located in the lower pole. Lymph node posterior to the right recurrent laryngeal nerve dissection is recommended for such tumors.

Universality and scaling in complex networks from periods of Chinese history.

Critical physical systems with large numbers of molecules can show universal and scaling behaviors. It is of interest to know whether human societies with large numbers of people can show the same behaviors. Here, we use network theory to analyze Chinese history in periods 209 BCE-23 CE and 515-618 CE) related to the Western Han-Xin Dynasty and the late Northern Wei-Sui Dynasty, respectively. Two persons are connected when they appear in the same historical event. We find that the historical networks from two periods separated about 500 years have interesting universal and scaling behaviors, and they are small-world networks; their average cluster coefficients as a function of degree are similar to the network of movie stars. In the historical networks, the persons with larger degrees prefer to connect with persons with a small degree; however, in the network of movie stars, the persons with larger degrees prefer to connect with persons with large degrees. We also find an interesting similar mechanism for the decline or collapse of historical Chinese dynasties. The collapses of the Xin dynasty (9-23 CE) and the Sui dynasty (581-618 CE) were initiated from their arrogant attitude toward neighboring states.

Circulating lnc-LOC as a novel noninvasive biomarker in the treatment surveillance of acute promyelocytic leukaemia.

BACKGROUND: Acute promyelocytic leukaemia (APL) is a unique subtype of acute myeloid leukaemia (AML) characterized by haematopoietic failure caused by the accumulation of abnormal promyelocytic cells in bone marrow (BM). However, indispensable BM biopsy frequently afflicts patients in leukaemia surveillance, which increases the burden on patients and reduces compliance. This study aimed to explore whether the novel circulating long noncoding RNA LOC100506453 (lnc-LOC) could be a target in diagnosis, assess the treatment response and supervise the minimal residual disease (MRD) of APL, thereby blazing a trail in noninvasive lncRNA biomarkers of APL. METHODS: Our study comprised 100 patients (40 with APL and 60 with non-APL AML) and 60 healthy donors. BM and peripheral blood (PB) sample collection was accomplished from APL patients at diagnosis and postinduction. Quantitative real-time PCR (qRT-PCR) was conducted to evaluate lnc-LOC expression. A receiver operating characteristic (ROC) analysis was implemented to analyse the value of lnc-LOC in the diagnosis of APL and treatment monitoring. For statistical analysis, the Mann-Whitney U test, a t test, and Spearman's rank correlation test were utilized. RESULTS: Our results showed that BM lnc-LOC expression was significantly different between APL and healthy donors and non-APL AML. lnc-LOC was drastically downregulated in APL patients' BM after undergoing induction therapy. Lnc-LOC was upregulated in APL cell lines and downregulated after all-trans retinoic acid (ATRA)-induced myeloid differentiation, preliminarily verifying that lnc-LOC has the potential to be considered a treatment monitoring biomarker. PB lnc-LOC was positively correlated with BM lnc-LOC in APL patients, non-APL AML patients and healthy donors and decreased sharply after complete remission (CR). However, upregulated lnc-LOC was manifested in relapsed-refractory patients. A positive correlation was revealed between PB lnc-LOC and PML-RARα transcript levels in BM samples. Furthermore, we observed a positive correlation between PB lnc-LOC and BM lnc-LOC expression in APL patients, suggesting that lnc-LOC can be utilized as a noninvasive biomarker for MRD surveillance. CONCLUSIONS: Our study demonstrated that PB lnc-LOC might serve as a novel noninvasive biomarker in the treatment surveillance of APL, and it innovated the investigation and application of newly found lncRNAs in APL noninvasive biomarkers used in diagnosis and detection.

RBCK1 is an endogenous inhibitor for triple negative breast cancer via hippo/YAP axis.

BACKGROUND: Triple negative breast cancer (TNBC) is one of the most lethal breast cancer subtypes. Due to a lack of effective therapeutic targets, chemotherapy is still the main medical treatment for TNBC patients. Thus, it is important and necessary to find new therapeutic targets for TNBC. Recent genomic studies implicated the Hippo / Yap signal is over activated in TNBC, manifesting it plays a key role in TNBC carcinogenesis and cancer progression. RBCK1 was firstly identified as an important component for linear ubiquitin assembly complex (LUBAC) and facilitates NFKB signaling in immune response. Further studies showed RBCK1 also facilitated luminal type breast cancer growth and endocrine resistance via trans-activation estrogen receptor alpha. METHODS: RBCK1 and YAP protein expression levels were measured by western blotting, while the mRNA levels of YAP target genes were measured by RT-PCR. RNA sequencing data were analyzed by Ingenuity Pathway Analysis. Identification of Hippo signaling activity was accomplished with luciferase assays, RT-PCR and western blotting. Protein stability assays and ubiquitin assays were used to detect YAP protein degradation. Ubiquitin-based immunoprecipitation assays were used to detect the specific ubiquitination modification on the YAP protein. RESULTS: In our current study, our data revealed an opposite function for RBCK1 in TNBC progression. RBCK1 over-expression inhibited TNBC cell progression in vitro and in vivo, while RBCK1 depletion promoted TNBC cell invasion. The whole genomic expression profiling showed that RBCK1 depletion activated Hippo/YAP axis. RBCK1 depletion increased YAP protein level and Hippo target gene expression in TNBC. The molecular biology studies confirmed that RBCK1 could bind to YAP protein and enhance the stability of YAP protein by promoting YAP K48-linked poly-ubiquitination at several YAP lysine sites (K76, K204 and K321). CONCLUSION: Our study revealed the multi-faced RBCK1 function in different subtypes of breast cancer patients and a promising therapeutic target for TNBC treatment. Video abstract.

TRIM3 facilitates estrogen signaling and modulates breast cancer cell progression.

BACKGROUND: Breast cancer is the most common cancer in women worldwide. More than 70% of breast cancers are estrogen receptor (ER) alpha positive. Compared with ER alpha-negative breast cancer, which is more aggressive and has a shorter survival time, ER alpha-positive breast cancer could benefit from endocrine therapy. Selective estrogen receptor modulators, such as tamoxifen, are widely used in endocrine therapy. Approximately half of ER alpha-positive breast cancer patients will eventually develop endocrine resistance, making it a major clinical challenge in therapy. Thus, decoding the throughput of estrogen signaling, including the control of ER alpha expression and stability, is critical for the improvement of breast cancer therapeutics. METHODS: TRIM3 and ER alpha protein expression levels were measured by western blotting, while the mRNA levels of ER alpha target genes were measured by RT-PCR. A CCK-8 assay was used to measure cell viability. RNA sequencing data were analyzed by Ingenuity Pathway Analysis. Identification of ER alpha signaling activity was accomplished with luciferase assays, RT-PCR and western blotting. Protein stability assays and ubiquitin assays were used to detect ER alpha protein degradation. Ubiquitin-based immunoprecipitation assays were used to detect the specific ubiquitination modification on the ER alpha protein. RESULTS: In our current study, we found that TRIM3, an E3 ligase, can promote ER alpha signaling activity and breast cancer progression. TRIM3 depletion inhibits breast cancer cell proliferation and migration, while unbiased RNA sequencing data indicated that TRIM3 is required for the activity of estrogen signaling on the -genome-wide scale. The immunoprecipitation assays indicated that TRIM3 associates with ER alpha and promotes its stability, possibly by inducing K63-linked polyubiquitination of ER alpha. In conclusion, our data implicate a nongenomic mechanism by which TRIM3 stabilizes the ER alpha protein to control ER alpha target gene expression linked to breast cancer progression. CONCLUSION: Our study provides a novel posttranslational mechanism in estrogen signaling. Modulation of TRIM3 expression or function could be an interesting approach for breast cancer treatment. Video abstract.

Triglyceride-glucose index is a predictive index of hyperuricemia events in elderly patients with hypertension: a cross-sectional study.

BACKGROUND: To analyze the association between triglyceride-glucose index (TYG index) and hyperuricemia (HUA) in elderly patients with hypertension. METHODS: A total of 428 inpatients with primary hypertension from March 2018 to March 2021 in Qinghai Provincial People's Hospital were retrospectively analyzed. Grouped by sex and serum uric acid. Serum uric acid (SUA), fasting blood glucose (FPG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), serum creatinine (Scr), urea nitrogen (BUN), triglycerides (TG), high-sensitivity C-reactive protein (HS-CRP) and other biochemical indicators were measured, and the TYG index was calculated. The TYG index and SUA levels of each group were compared, and the correlation between TYG index and hyperuricemia was analyzed. Multivariate Logistic regression was performed to analyze the relationship between TYG index and the risk of HUA in elderly patients with hypertension. The ROC curve was used to evaluate the predictive value of TYG index in elderly patients with hypertension associated with HUA. RESULTS: TYG index was significantly higher in the HUA group than in the normal group in both men and women (P < .05). Spearson correlation analysis showed that TYG index positively correlated with TC, TG, FPG, SUA, and LDL-C(r = 0.327, 0.975, 0.412, 0.214, 0.215, P = .000, 0.000, 0.000, 0.000, 0.000), and negatively correlated with age and HDL-C (r = -0.166, -0.248, P = .001, 0.000). Logistic regression analysis showed that Scr, BUN, HS-CRP and TYG index were the risk factors for HUA in elderly patients with hypertension (P < .05).The ROC curve showed an area under the TYG exponential curve of 0.617(95%CI:0.561 ~ 0.673) with a sensitivity of 64.4% and a specificity of 57.4%. CONCLUSION: TYG index in elderly hypertensive patients is closely related to hyperuricemia, and the increase of TYG index is an independent risk factor for HUA in elderly hypertensive patients.

Irregular spots on body surfaces of vertebrates induced by supercritical pitchfork bifurcations.

The classical Turing mechanism containing a long-range inhibition and a short-range self-enhancement provides a type of explanation for the formation of patterns on body surfaces of some vertebrates, e.g., zebras, giraffes, and cheetahs. For other type of patterns (irregular spots) on body surfaces of some vertebrates, e.g., loaches, finless eels, and dalmatian dogs, the classical Turing mechanism no longer applies. Here, we propose a mechanism, i.e., the supercritical pitchfork bifurcation, which may explain the formation of this type of irregular spots, and present a method to quantify the similarity of such patterns. We assume that, under certain conditions, the only stable state of "morphogen" loses its stability and transitions to two newly generated stable states with the influence of external noise, thus producing such ruleless piebald patterns in space. The difference between the competitiveness of these two states may affect the resulting pattern. Moreover, we propose a mathematical model based on this conjecture and obtain this type of irregular patterns by numerical simulation. Furthermore, we also study the influence of parameters in the model on pattern structures and obtain the corresponding pattern structures of some vertebrates in nature, which verifies our conjecture.

Epidemic dynamics on higher-dimensional small world networks.

Dimension governs dynamical processes on networks. The social and technological networks which we encounter in everyday life span a wide range of dimensions, but studies of spreading on finite-dimensional networks are usually restricted to one or two dimensions. To facilitate investigation of the impact of dimension on spreading processes, we define a flexible higher-dimensional small world network model and characterize the dependence of its structural properties on dimension. Subsequently, we derive mean field, pair approximation, intertwined continuous Markov chain and probabilistic discrete Markov chain models of a COVID-19-inspired susceptible-exposed-infected-removed (SEIR) epidemic process with quarantine and isolation strategies, and for each model identify the basic reproduction number R 0 , which determines whether an introduced infinitesimal level of infection in an initially susceptible population will shrink or grow. We apply these four continuous state models, together with discrete state Monte Carlo simulations, to analyse how spreading varies with model parameters. Both network properties and the outcome of Monte Carlo simulations vary substantially with dimension or rewiring rate, but predictions of continuous state models change only slightly. A different trend appears for epidemic model parameters: as these vary, the outcomes of Monte Carlo change less than those of continuous state methods. Furthermore, under a wide range of conditions, the four continuous state approximations present similar deviations from the outcome of Monte Carlo simulations. This bias is usually least when using the pair approximation model, varies only slightly with network size, and decreases with dimension or rewiring rate. Finally, we characterize the discrepancies between Monte Carlo and continuous state models by simultaneously considering network efficiency and network size.

Diagnosis, treatment and genetic analysis of a case of Alstrom syndrome caused by compoud heterozygous mutation of ALMS1.

Alstrom syndrome is a rare autosomal recessive disorder disease caused by mutations in the ALMS1 gene, and its typical clinical manifestations include cone-rod retinal dystrophy, sensorineural deafness, obesity, insulin resistance, diabetes mellitus, hypertriglyceridemia, non-alcoholic fatty liver, dilated cardiomyopathy, and progressive hepatic and renal dysfunction. In this report, we followed up a young male patient presenting with diabetes mellitus, who was later diagnosed with blindness, deafness, hyperlipidemia, obesity, fatty liver, and insulin resistance. Genetic testing revealed a compound heterozygous mutation in ALMS1 from the patient, with an exon 8 c.5535delG (p.S1847Lfs*24) mutation inherited from the maternal side and an exon 16 c.10819C>T (p.R3607X) mutation from the paternal side. Neither of these two mutations had been previously recorded in the known ALMS1 genetic mutation database. Hyperinsulinemic-euglycemic clamp test indicated that the insulin sensitivity index was significantly improved in the patient after taking oral dapagliflozin. By summarizing and analyzing this case, we should consider Alstrom syndrome in clinical adolescent-onset diabetes patients with blindness, deafness, severe insulin resistance, and lipid metabolism disorder. These two new mutation sites identified in this case enrich the genetic mutation database of the ALMS1 gene, and the follow-up data of this study provide new evidence for deciding appropriate glucose-lowering regimens in patients with Alstrom syndrome.

ZNF213 negatively controls triple negative breast cancer progression via Hippo/YAP signaling.

Breast cancer is one of the most commonly diagnosed malignancies worldwide, while the triple negative breast cancer (TNBC) is the most aggressive and virulent subtype in breast cancers. Compared with luminal type breast cancers, which could be well controlled by endocrine treatment, TNBC is worse in prognosis and lack of effective targeted therapy. Thus, it would be interesting and meaningful to identify novel therapeutic targets for TNBC treatments. Recent genomic data showed the activation of Hippo/YAP signaling in TNBC, indicating its critical roles in TNBC carcinogenesis and cancer progression. Hippo/YAP signaling could subject to several kinds of protein modifications, including ubiquitination and phosphorylation. Quite a few studies have demonstrated these modifications, which controlled YAP protein stability and turnover, played critical role in Hippo signaling activation In our current study, we identified ZNF213 as a negative modifier for Hippo/YAP axis. ZNF213 depletion promoted TNBC cell migration and invasion, which could be rescued by further YAP silencing. ZNF213 knocking down facilitated YAP protein stability and Hippo target gene expression, including CTGF and CYR61. Further mechanism studies demonstrated that ZNF213 associated with YAP and facilitated YAP K48-linked poly-ubiquitination at several YAP lysine sites (K252, K254, K321 and K497). Besides, the clinical data showed that ZNF213 negatively correlated with YAP protein level and Hippo target gene expression in TNBC samples. ZNF213 expression correlated with good prognosis in TNBC patients. Our data provided novel insights in YAP proteolytic regulation and TNBC progression.

Visibility-graphlet approach to the output series of a Hodgkin-Huxley neuron.

The output signals of neurons that are exposed to external stimuli are of great importance for brain functionality. Traditional time-series analysis methods have provided encouraging results; however, the associated patterns and their correlations in the output signals of neurons are masked by statistical procedures. Here, graphlets are employed to extract the local temporal patterns and the transitions between them from the output signals when neurons are exposed to external stimuli with selected stimulating periods. A transition network is defined where the node is the graphlet and the direct link is the transition between two successive graphlets. The transition-network structure is affected by the simulating periods. When the stimulating period moves close to an integer multiple of the neuronal intrinsic period, only the backbone or core survives, while the other linkages disappear. Interestingly, the size of the backbone (number of nodes) equals the multiple. The transition-network structure is conservative within each stimulating region, which is defined as the range between two successive integer multiples. Nevertheless, the backbone or detailed structure is significantly altered between different stimulating regions. This alternation is induced primarily from a total of 12 active linkages. Hence, the transition network shows the structure of cross correlations in the output time-series for a single neuron.

Consumption of ultra-processed foods and health outcomes: a systematic review of epidemiological studies.

BACKGROUND: Consumption of ultra-processed foods (UPFs) plays a potential role in the development of obesity and other diet-related noncommunicable diseases (NCDs), but no studies have systematically focused on this. This study aimed to summarize the evidence for the association between UPFs consumption and health outcomes. METHODS: A comprehensive search was conducted in PubMed, Embase, and Web of Science to identify all relevant studies. Epidemiological studies were included, and identified studies were evaluated for risk of bias.A narrative review of the synthesized findings was provided to assess the association between UPFs consumption and health outcomes. RESULTS: 20 studies (12 cohort and 8 cross-sectional studies) were included in the analysis, with a total of 334,114 participants and 10 health outcomes. In a narrative review, high UPFs consumption was obviously associated with an increased risk of all-cause mortality, overall cardiovascular diseases, coronary heart diseases, cerebrovascular diseases, hypertension, metabolic syndrome, overweight and obesity, depression, irritable bowel syndrome, overall cancer, postmenopausal breast cancer, gestational obesity, adolescent asthma and wheezing, and frailty. It showed no significant association with cardiovascular disease mortality, prostate and colorectal cancers, gestational diabetes mellitus and gestational overweight. CONCLUSIONS: This study indicated a positive association between UPFs consumption and risk of several health outcomes. Large-scale prospective designed studies are needed to confirm our findings.