Food avoidance is associated with reduced dentitions and edentulousness

Objectives

To investigate associations between food avoidance and dental status, age, gender, and socio-economic status (SES).

Materials and methods

The Chinese sample comprised 1463 dentulous (≥ 1 tooth in each jaw) and 124 edentulous (in one or both jaws) participants aged ≥ 40 yrs. The Vietnamese sample comprised 2820 dentulous and 253 edentulous participants aged ≥ 20 yrs. Food avoidance due to chewing difficulties was scored for regionally common 4 soft and 4 hard foods. Dental status was classified according to the multi-level hierarchical dental functional classification system (HDFC) based on the number and location of teeth and posterior occlusal pairs. Associations were analyzed using multivariate logistic regression analyses.

Results

For dentulous participants, the chance of avoiding foods was significantly larger with < 10 teeth in each jaw (OR = 2.26 (Chinese sample), respectively 1.74 (Vietnamese sample)), incomplete anterior region (OR = 1.78, respectively 1.84), “impaired” premolar region (OR = 2.22, respectively 1.71), or “impaired” molar region (OR = 2.46, respectively 1.84). Edentulous participants had twice the chance of avoiding foods (OR = 2.01 respectively 2.20). Avoiding foods was significantly associated with higher age. Participants of low SES (Chinese sample, OR = 1.93) and females (Vietnamese sample, OR = 1.27) had a larger chance of avoiding foods.

Conclusions

Avoiding foods was significantly associated with reduced dentitions, edentulousness, and higher age; low SES only in the Chinese and being female only in the Vietnamese sample.

Clinical relevance

Incomplete anterior regions, “impaired” premolar or molar regions, and especially edentulousness can be considered significant risk indicators for food avoidance.

     

Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters

Recent genomic studies challenge the conventional model that each metastasis must arise from a single tumor cell and instead reveal that metastases can be composed of multiple genetically distinct clones. These intriguing observations raise the question: How do polyclonal metastases emerge from the primary tumor? In this study, we used multicolor lineage tracing to demonstrate that polyclonal seeding by cell clusters is a frequent mechanism in a common mouse model of breast cancer, accounting for >90% of metastases. We directly observed multicolored tumor cell clusters across major stages of metastasis, including collective invasion, local dissemination, intravascular emboli, circulating tumor cell clusters, and micrometastases. Experimentally aggregating tumor cells into clusters induced a >15-fold increase in colony formation ex vivo and a >100-fold increase in metastasis formation in vivo. Intriguingly, locally disseminated clusters, circulating tumor cell clusters, and lung micrometastases frequently expressed the epithelial cytoskeletal protein, keratin 14 (K14). RNA-seq analysis revealed that K14⁺ cells were enriched for desmosome and hemidesmosome adhesion complex genes, and were depleted for MHC class II genes. Depletion of K14 expression abrogated distant metastases and disrupted expression of multiple metastasis effectors, including Tenascin C (Tnc), Jagged1 (Jag1), and Epiregulin (Ereg). Taken together, our findings reveal K14 as a key regulator of metastasis and establish the concept that K14⁺ epithelial tumor cell clusters disseminate collectively to colonize distant organs.During metastasis, cancer cells escape the primary tumor, travel through the circulation, and colonize distant organs. Conventional models of cancer progression propose that each metastasis arises from the clonal outgrowth of a single tumor cell and this conceptual framework is a foundation for models, such as epithelial-mesenchymal transition (EMT) and migratory cancer stem cells (1).Challenging the generality of the single-cell/single-metastasis model are long-standing clinical observations that tumor cell clusters (also termed “tumor clumps”) are also observed across the stages of metastasis. Tumor cell clusters are detected in the bloodstream of cancer patients (2), clusters can efficiently seed metastases (3), and though rare, circulating tumor cell (CTC) clusters have prognostic significance (4, 5). Furthermore, metastases are composed of multiple genetically distinct tumor cell clones, in mouse models of breast, pancreas, and small cell carcinoma (5–7), and in human metastatic prostate cancer patients (8). Taken together, these observations provide accumulating evidence that tumor cell clusters contribute to metastasis. However, they leave unresolved two important questions: how do tumor cell clusters emerge from the primary tumor, and which molecular features identify cell clusters that metastasize?An important clinical observation is that cancer cells invade the surrounding stroma as cohesive clusters in the majority of epithelial tumors, a process termed “collective invasion” (9, 10). In breast cancer, collective invasion is facilitated by invasive leader cells, a subpopulation of tumor cells that highly express keratin 14 (K14) and other basal epithelial markers (11). K14⁺ cells are migratory, protrusive, and lead trailing K14⁻ cells, while maintaining cell–cell cohesion and E-cadherin–based cell contacts.In this study, we sought to understand how these K14⁺ cells exit collective invasion strands in the primary tumor and travel to distant organs (12). One hypothesis is that collective invasion is an intermediate step toward eventual single-cell dissemination and monoclonal metastasis. However, tumor cell clusters are detected in circulation (5) and primary human breast tumors can disseminate collectively into the surrounding extracellular matrix in ex vivo assays (13–15). These data prompted an alternative hypothesis, that collectively invading K14⁺ cancer cells could initiate and complete the metastatic process as a cohesive multicellular unit. Here we define the clonal nature of metastases in a spontaneous mouse model of metastasis to the lungs (16, 17), in which the predominant invasive form in the primary tumor is collective invasion strands led by K14⁺ cells (11). We establish that the majority of metastases arise from polyclonal seeds, and show that disseminated tumor cell clusters are predominantly composed of K14⁺ cells. We propose a mechanism for polyclonal metastasis via the collective invasion, dissemination, and colonization of clusters of K14⁺ cancer cells.     

A temporal requirement for Hippo signaling in mammary gland differentiation,growth, and tumorigenesis

Despite recent progress, the physiological role of Hippo signaling in mammary gland development and tumorigenesis remains poorly understood. Here we show that the Hippo pathway is functionally dispensable in virgin mammary glands but specifically required during pregnancy. In contrast to many other tissues, hyperactivation of YAP in mammary epithelia does not induce hyperplasia but leads to defects in terminal differentiation. Interestingly, loss of YAP causes no obvious defects in virgin mammary glands but potently suppresses oncogene-induced mammary tumors. The selective requirement for YAP in oncogenic growth highlights the potential of YAP inhibitors as molecular targeted therapies against breast cancers.     

From the Cover: Synchronization in human musical rhythms and mutually interacting complex systems

Though the music produced by an ensemble is influenced by multiple factors, including musical genre, musician skill, and individual interpretation, rhythmic synchronization is at the foundation of musical interaction. Here, we study the statistical nature of the mutual interaction between two humans synchronizing rhythms. We find that the interbeat intervals of both laypeople and professional musicians exhibit scale-free (power law) cross-correlations. Surprisingly, the next beat to be played by one person is dependent on the entire history of the other person’s interbeat intervals on timescales up to several minutes. To understand this finding, we propose a general stochastic model for mutually interacting complex systems, which suggests a physiologically motivated explanation for the occurrence of scale-free cross-correlations. We show that the observed long-term memory phenomenon in rhythmic synchronization can be imitated by fractal coupling of separately recorded or synthesized audio tracks and thus applied in electronic music. Though this study provides an understanding of fundamental characteristics of timing and synchronization at the interbrain level, the mutually interacting complex systems model may also be applied to study the dynamics of other complex systems where scale-free cross-correlations have been observed, including econophysics, physiological time series, and collective behavior of animal flocks.In his book Musicophilia, neurologist Oliver Sacks writes: “In all societies, a primary function of music is collective and communal, to bring and bind people together. People sing together and dance together in every culture, and one can imagine them having done so around the first fires, a hundred thousand years ago” (1). Sacks adds, “In such a situation, there seems to be an actual binding of nervous systems accomplished by rhythm” (2). These thoughts lead to the question: Is there any underlying and quantifiable structure to the subjective experience of “musical binding”? Here, we examine the statistical nature of musical binding (also referred to as musical coupling) when two humans play rhythms in synchrony.Every beat a single (noninteracting) layperson or musician plays is accompanied by small temporal deviations from the exact beat pattern, i.e., even a trained musician will hit a drum beat slightly ahead or behind the metronome (with a SD of typically 5–15 ms). Interestingly, these deviations are statistically dependent and exhibit long-range correlations (LRC) (3, 4). Listeners significantly prefer music mirroring long-range correlated temporal deviations over uncorrelated (white noise) fluctuations (5, 6). LRC are also inherent in the reproduction of both spatial and temporal intervals of single subjects (4, 7–9) and in musical compositions, such as pitch fluctuations (a simple example of pitch fluctuations is a melody) (10, 11) and note lengths (12). The observation of power law correlations in fluctuations of pitch and note length in compositions reflects a hierarchical, self-similar structure in these compositions.In this article, we examine rhythmic synchronization, which is at the foundation of musical interaction, from orchestral play to audience hand-clapping (13). More specifically, we show that the interbeat intervals (IBIs) of two subjects synchronizing musical rhythms exhibit long-range cross-correlations (LRCCs), which appears to be a general phenomenon given that these LRCC were found both in professional musicians and in laypeople.The observation of LRCCs may point to characteristics of criticality in the dynamics of the considered complex system. LRCCs are characterized by a power law decay of the cross-correlation function and indicate that the two time series of IBIs form a self-similar (fractal) structure. Here, self-similarity implies that trends in the IBIs are likely to repeat on different timescales, i.e., patterns of IBI fluctuations of one musician tend to reproduce in a statistically similar way at a later time—even in the other musician’s play. A variety of complex systems exhibit LRCCs; examples include price fluctuations of the New York Stock Exchange (where the LRCCs become more pronounced during economic crises) (14–16), heartbeat and EEG fluctuations (15, 17), particles in a Lorentz channel (18), the binding affinity of proteins to DNA (15), schools of fish (19), and the collective response of starling flocks (20, 21). The origin of collective dynamics and LRCCs based on local interactions often appears elusive (20), and is the focus of current research (19, 21). Of particular interest are the rules of interactions of the individuals in a crowd (22, 23) and transitions to synchronized behavior (16, 24). We introduce a stochastic model for mutually interacting complex systems (MICS) that generates LRCCs and provides a physiologically motivated explanation for the surprising presence of long-term memory in the cross-correlations of musical performances.Interbrain synchronization has received growing attention recently, including studies of interpersonal synchronization (see ref. 4 for an overview), coordination of speech rhythm (25), social interactions (26), cortical phase synchronization while playing guitar in duets (27, 28), and improvisation in classical music performances (29).Notably, the differences between the beats of two musicians are on the order of only a few milliseconds, not much larger than the typical duration of a single action potential (∼1 ms). The neurophysical mechanisms of timing in the millisecond range are still widely open (30, 31). EEG oscillatory patterns are associated with error prediction during music performance (32). Fine motor skills, such as finger-tapping rhythm and rate, are used to establish an early diagnosis of Huntington disease (33). The neurological capacity to synchronize with a beat may offer therapeutic applications for Parkinson disease, but the mechanisms are unknown to date (34). This study offers a statistical framework that may help to understand these mechanisms.     

Redox-dependent complex formation by an ATP-dependent activator of the corrinoid/iron-sulfur protein

Movement, cell division, protein biosynthesis, electron transfer against an electrochemical gradient, and many more processes depend on energy conversions coupled to the hydrolysis of ATP. The reduction of metal sites with low reduction potentials (E^0′ < -500 mV) is possible by connecting an energetical uphill electron transfer with the hydrolysis of ATP. The corrinoid-iron/sulfur protein (CoFeSP) operates within the reductive acetyl-CoA pathway by transferring a methyl group from methyltetrahydrofolate bound to a methyltransferase to the [Ni-Ni-Fe₄S₄] cluster of acetyl-CoA synthase. Methylation of CoFeSP only occurs in the low-potential Co(I) state, which can be sporadically oxidized to the inactive Co(II) state, making its reductive reactivation necessary. Here we show that an open-reading frame proximal to the structural genes of CoFeSP encodes an ATP-dependent reductive activator of CoFeSP. Our biochemical and structural analysis uncovers a unique type of reductive activator distinct from the electron-transferring ATPases found to reduce the MoFe-nitrogenase and 2-hydroxyacyl-CoA dehydratases. The CoFeSP activator contains an ASKHA domain (acetate and sugar kinases, Hsp70, and actin) harboring the ATP-binding site, which is also present in the activator of 2-hydroxyacyl-CoA dehydratases and a ferredoxin-like [2Fe-2S] cluster domain acting as electron donor. Complex formation between CoFeSP and its activator depends on the oxidation state of CoFeSP, which provides evidence for a unique strategy to achieve unidirectional electron transfer between two redox proteins.Energy transduction is fundamental for life. Aerobic and anaerobic organisms depend on coupling ATP hydrolysis to movement, activation of metabolites, or peptide bond formation, among others. Several metal-containing enzymes, such as nitrogenase, radical-dependent β,α-dehydratases, the related benzoyl-CoA reductases, and different cobalamin-dependent methyltransferases are able to convert unreactive molecules by acting in a low-potential regime. The highly energetic electrons required for these reactions (1–3) are injected by ATPases that enable the transfer of electrons against the redox potential gradient, driven by the hydrolysis of ATP. Three different types of reductive metallo-ATPase have been described so far.The enzyme nitrogenase is by reducing dinitrogen with six electrons to ammonia at the heart of the global nitrogen cycle (1, 4, 5). Nitrogenase consists of the dinitrogenase, also called MoFe protein for the predominant Mo-containing variant, and the dinitrogenase reductase, called Fe protein (1, 4–6). The Fe protein is a homodimer covalently linked through a [4Fe-4S] cluster bound within the dimer interface. Both monomers are able to bind and hydrolyze ATP in a cleft containing a P loop. For electron transfer (ET) between Fe and MoFe proteins to occur, the reduced Fe protein binds MgATP and forms a complex with the MoFe protein positioning the electron-donating [4Fe-4S] cluster and electron-accepting P cluster within the typical limits for physiological ET (< 15 Å) (1, 4, 7, 8). Hydrolysis of two ATP molecules initiates a one-electron transfer between both partners (9, 10). Conformational changes of the Fe protein induced by ATP hydrolysis are believed to act as switches for the association/dissociation of the Fe:MoFe protein complex and the delivery of electrons (8–11). The Fe protein is bifunctional and also acts as a molybdate/homocitrate insertase during the maturation of nitrogenase (5, 12).Benzoyl CoA reductases and 2-hydroxyacyl CoA dehydratases rely on homologous metallo-ATPases to catalyze the reduction of benzoyl-CoA or the β/α-dehydration of 2-hydroxyacyl-CoA compounds via formation of ketyl radicals (2). The structure of the homodimeric activator of 2-hydroxyglutaryl-CoA dehydratase revealed a [4Fe-4S] cluster covalently linking the two monomers, on a first glance resembling the Fe protein (13). The structure of the activator also showed it to be a member of the ASKHA (acetate and sugar kinases/heat shock protein 70/actin) superfamily. ASKHA proteins catalyze phosphoryl transfers or hydrolysis of ATP in a variety of biological contexts and are distinct from the P loop containing switch-type NTPases to which the Fe protein of nitrogenase belongs (13, 14). The binding of two MgATP molecules to the reduced activator is supposed to induce a conformational change and drives formation of the complex with the dehydratase. ATP hydrolysis likely increases the reducing power of the reduced [4Fe-4S] cluster of the activator, enabling the one-electron transfer to the low-potential [4Fe-4S] cluster of the dehydratase (2, 15). Unlike the 2-hydroxyacyl-CoA dehydratase system, the reduction of benzoyl-CoA is a two-step ET requiring a stoichiometric consumption of ATP (3).Recently, a third class of electron-transferring metallo-ATPases has been discovered (16–18). This enzyme class belongs to the COG3894 protein family and has been termed reductive activases for corrinoid enzymes (RACE) (17). The genome of several anaerobic microorganisms, which encode corrinoid-dependent methyltransferases and enzymes of the reductive acetyl-CoA pathway, also encode for proteins homologous to the two investigated RACE proteins with their characteristic binding motifs for one Fe/S cluster (17, 18). Bacterial RACE proteins typically show [2Fe-2S] cluster-binding-motifs, as in the veratrol O-demethylase system of Acetobacterium dehalogenans (16), whereas in archaea, as in the activator of the methylamine methyltransferase of the methanogenic archaeon Methanosarcina barkeri [4Fe-4S] cluster-binding motifs are more abundant (17, 18).The anaerobic hydrogenogenic bacterium Carboxydothermus hydrogenoformans is able to convert CO₂ into cellular carbon compounds via the reductive acetyl-CoA pathway (also known as the Wood–Ljungdahl pathway) (19–21). The corrinoid/iron-sulfur protein (CoFeSP) connects the methyl and carbonyl branch of this pathway by accepting a methyl group from methyltetrahydrofolate bound to a methyltransferase and donating it to the Ni,Fe-containing acetyl-CoA synthase (22, 23). Three redox states are known for the corrinoid cofactor of CoFeSP: The nucleophilic Co(I) acts as a methyl-acceptor, Co(II) is an oxidized inactive state, and CH₃ - Co(III) acts as the methyl donor of acetyl-CoA synthase (22, 23). The occasional oxidation of Co(I) to Co(II) inactivates CoFeSP, which has to be reactivated by a one-electron reduction (23, 24). The low midpoint potential needed to reduce Co²⁺ to Co¹⁺ (< -504 mV at pH 7.4) (25) can be achieved in vitro using either chemical reducing agents such as Na-dithionite (DT), Ti³⁺ citrate, via photoreduction with deazariboflavin as a catalyst or enzymatically with electrons generated by the oxidation of CO to CO₂ by carbon monoxide dehydrogenase (22, 26). An ATP-dependent reactivation of CoFeSP has not been reported so far.An open reading frame (orf7), situated between the structural genes coding for the CoFeSP subunits CfsA and CfsB of Moorella thermoacetica (27), codes for a member of the COG3894 protein family and contains the putative [2Fe-2S] cluster-binding motif CX₅CX₂CX_nC (17, 18). The genome of C. hydrogenoformans contains a similar arrangement of genes coding for enzymes of the reductive acetyl-CoA pathway as M. thermoacetica, including a homolog of Orf7 (CHY_1224 assigned as COG3894). To test whether an ATP-dependent reductive activator is operative in the reductive acetyl-CoA pathway, we established the heterologous production of the Orf7 homolog and investigated its activity, structure, and selective complex formation with CoFeSP. Furthermore, we reveal its relationship to known ATPases including the activator of 2-hydroxyacyl-CoA dehydratases and compare its strategy to achieve unidirectional electron transport with the other types of ATP-dependent activators/reductases.     

Dental functional status with and without tooth replacement in a Chinese adult population

The objective of this study is to investigate the prevalence of missing teeth and prosthodontic replacements in a Chinese adult population using a hierarchical dental functional classification system. A total of 1,462 dentate subjects over 40 years from Shandong Province, China were included and categorized in the functional classification system with and without tooth replacements. Depending on replacements, subjects could be reclassified (promoted) to categories reflecting higher functionality. "Promotions" were considered indicators for prosthodontic effectiveness. Homogeneities after dichotomization into functional categories appeared to be moderate to good. In the "≥10 teeth in each jaw" branch, mean number of teeth and posterior occluding pairs were 27.93 ± 2.74 and 7.10 ± 1.94, respectively. In the branch "<10 teeth in each jaw," these figures were 16.17 ± 5.54 and 1.49 ± 1.45. Fixed dental prostheses (FDPs) added on average 3.5 artificial teeth; 46% of subjects with FDP promoted to a higher functional level. For removable dental prostheses (RDPs), these numbers were 8.5% and 79%, respectively. Promotion value per tooth added was significantly higher for FDPs. The classification system was able to quantify the effectiveness of teeth replacements. It was shown that RDPs were more effective when higher numbers of teeth were replaced, while FDPs were more effective per artificial tooth added.