Effects of methylation and transcription factor YY1 on ID2 expression in non-small cell lung carcinoma cells.

The inhibitor of DNA-binding 2 (ID2) plays a major role in tumor dedifferentiation in non-small cell lung cancer (NSCLC). Studies have indicated an inverse correlation between ID2 expression and NSCLC cell invasiveness. However, the mechanisms through which ID2 activation is regulated are currently unclear. We overexpressed ID2 in H1299 cells and extensively characterized their cellular behaviors. By employing a serial deletion approach combined with a reporter assay, we pinpointed the basal promoter region of ID2. We also examined the DNA methylation status of the ID2 promoter to elucidate the epigenetic mechanisms driving ID2 regulation. Our results revealed that ID2 overexpression effectively inhibited the migration, invasion, proliferation, and colony formation abilities of H1299 cells. The region from -243 to +202 played a major role in driving the transcriptional activity of ID2. Sequence analysis results indicated that the transcription factor Yin Yang 1 (YY1) might be crucial in the regulation of ID2 expression. The ectopically expressed YY1 activated both the expression levels of ID2 and the transcriptional activity of the ID2 promoter, potentially contributing to its repressive activity on cancer cell growth. Furthermore, site-directed mutagenesis and chromatin immunoprecipitation assays revealed that YY1 may target the -120 and -76 sites of the ID2 promoter, thereby activating its transcriptional activity. The ID2 promoter regions were also fully methylated in CL1-5 cells, and the methylation level was correlated with the expression levels of the ID2 promoter. Moreover, the YY1-induced suppression of colony formation was counteracted by ID2 knockdown, which suggests that YY1 represses cell colony growth through the regulation of ID2. Our results indicate that YY1 plays a role in transactivating ID2 expression and might also contribute to the repression of colony growth through the regulation of ID2.

Adaptation of a eukaryote-like ProRS to a prokaryote-like tRNAPro.

Prolyl-tRNA synthetases (ProRSs) are unique among aminoacyl-tRNA synthetases (aaRSs) in having two distinct structural architectures across different organisms: prokaryote-like (P-type) and eukaryote/archaeon-like (E-type). Interestingly, Bacillus thuringiensis harbors both types, with P-type (BtProRS1) and E-type ProRS (BtProRS2) coexisting. Despite their differences, both enzymes are constitutively expressed and functional in vivo. Similar to BtProRS1, BtProRS2 selectively charges the P-type tRNAPro and displays higher halofuginone tolerance than canonical E-type ProRS. However, these two isozymes recognize the primary identity elements of the P-type tRNAPro-G72 and A73 in the acceptor stem-through distinct mechanisms. Moreover, BtProRS2 exhibits significantly higher tolerance to stresses (such as heat, hydrogen peroxide, and dithiothreitol) than BtProRS1 does. This study underscores how an E-type ProRS adapts to a P-type tRNAPro and how it may contribute to the bacterium's survival under stress conditions.

Micrococcin cysteine-to-thiazole conversion through transient interactions between the scaffolding protein TclI and the modification enzymes TclJ and TclN.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a broad group of compounds mediating microbial competition in nature. Azole/azoline heterocycle formation in the peptide backbone is a key step in the biosynthesis of many RiPPs. Heterocycle formation in RiPP precursors is often carried out by a scaffold protein, an ATP-dependent cyclodehydratase, and an FMN-dependent dehydrogenase. It has generally been assumed that the orchestration of these modifications is carried out by a stable complex including the scaffold, cyclodehydratase, and dehydrogenase. The antimicrobial RiPP micrococcin begins as a precursor peptide (TclE) with a 35-amino acid N-terminal leader and a 14-amino acid C-terminal core containing six Cys residues that are converted to thiazoles. The putative scaffold protein (TclI) presumably presents the TclE substrate to a cyclodehydratase (TclJ) and a dehydrogenase (TclN) to accomplish the two-step installation of the six thiazoles. In this study, we identify a minimal TclE leader region required for thiazole formation, demonstrate complex formation between TclI, TclJ, and TclN, and further define regions of these proteins required for complex formation. Our results point to a mechanism of thiazole installation in which TclI associates with the two enzymes in a mutually exclusive fashion, such that each enzyme competes for access to the peptide substrate in a dynamic equilibrium, thus ensuring complete modification of each Cys residue in the TclE core. IMPORTANCE: Thiopeptides are a family of antimicrobial peptides characterized for having sulfur-containing heterocycles and for being highly post-translationally modified. Numerous thiopeptides have been identified; almost all of which inhibit protein synthesis in gram-positive bacteria. These intrinsic antimicrobial properties make thiopeptides promising candidates for the development of new antibiotics. The thiopeptide micrococcin is synthesized by the ribosome and undergoes several post-translational modifications to acquire its bioactivity. In this study, we identify key interactions within the enzymatic complex that carries out cysteine to thiazole conversion in the biosynthesis of micrococcin.

Machine learning-based longitudinal prediction for GJB2-related sensorineural hearing loss.

BACKGROUND: Recessive GJB2 variants, the most common genetic cause of hearing loss, may contribute to progressive sensorineural hearing loss (SNHL). The aim of this study is to build a realistic predictive model for GJB2-related SNHL using machine learning to enable personalized medical planning for timely intervention. METHOD: Patients with SNHL with confirmed biallelic GJB2 variants in a nationwide cohort between 2005 and 2022 were included. Different data preprocessing protocols and computational algorithms were combined to construct a prediction model. We randomly divided the dataset into training, validation, and test sets at a ratio of 72:8:20, and repeated this process ten times to obtain an average result. The performance of the models was evaluated using the mean absolute error (MAE), which refers to the discrepancy between the predicted and actual hearing thresholds. RESULTS: We enrolled 449 patients with 2184 audiograms available for deep learning analysis. SNHL progression was identified in all models and was independent of age, sex, and genotype. The average hearing progression rate was 0.61 dB HL per year. The best MAE for linear regression, multilayer perceptron, long short-term memory, and attention model were 4.42, 4.38, 4.34, and 4.76 dB HL, respectively. The long short-term memory model performed best with an average MAE of 4.34 dB HL and acceptable accuracy for up to 4 years. CONCLUSIONS: We have developed a prognostic model that uses machine learning to approximate realistic hearing progression in GJB2-related SNHL, allowing for the design of individualized medical plans, such as recommending the optimal follow-up interval for this population.

Deciphering DED assembly mechanisms in FADD-procaspase-8-cFLIP complexes regulating apoptosis.

Fas-associated protein with death domain (FADD), procaspase-8, and cellular FLICE-inhibitory proteins (cFLIP) assemble through death-effector domains (DEDs), directing death receptor signaling towards cell survival or apoptosis. Understanding their three-dimensional regulatory mechanism has been limited by the absence of atomic coordinates for their ternary DED complex. By employing X-ray crystallography and cryogenic electron microscopy (cryo-EM), we present the atomic coordinates of human FADD-procaspase-8-cFLIP complexes, revealing structural insights into these critical interactions. These structures illustrate how FADD and cFLIP orchestrate the assembly of caspase-8-containing complexes and offer mechanistic explanations for their role in promoting or inhibiting apoptotic and necroptotic signaling. A helical procaspase-8-cFLIP hetero-double layer in the complex appears to promote limited caspase-8 activation for cell survival. Our structure-guided mutagenesis supports the role of the triple-FADD complex in caspase-8 activation and in regulating receptor-interacting protein kinase 1 (RIPK1). These results propose a unified mechanism for DED assembly and procaspase-8 activation in the regulation of apoptotic and necroptotic signaling across various cellular pathways involved in development, innate immunity, and disease.

Adaptive evolution: Eukaryotic enzyme's specificity shift to a bacterial substrate.

Prolyl-tRNA synthetase (ProRS), belonging to the family of aminoacyl-tRNA synthetases responsible for pairing specific amino acids with their respective tRNAs, is categorized into two distinct types: the eukaryote/archaeon-like type (E-type) and the prokaryote-like type (P-type). Notably, these types are specific to their corresponding cognate tRNAs. In an intriguing paradox, Thermus thermophilus ProRS (TtProRS) aligns with the E-type ProRS but selectively charges the P-type tRNAPro, featuring the bacterium-specific acceptor-stem elements G72 and A73. This investigation reveals TtProRS's notable resilience to the inhibitor halofuginone, a synthetic derivative of febrifugine emulating Pro-A76, resembling the characteristics of the P-type ProRS. Furthermore, akin to the P-type ProRS, TtProRS identifies its cognate tRNA through recognition of the acceptor-stem elements G72/A73, along with the anticodon elements G35/G36. However, in contrast to the P-type ProRS, which relies on a strictly conserved R residue within the bacterium-like motif 2 loop for recognizing G72/A73, TtProRS achieves this through a non-conserved sequence, RTR, within the otherwise non-interacting eukaryote-like motif 2 loop. This investigation sheds light on the adaptive capacity of a typically conserved housekeeping enzyme to accommodate a novel substrate.

Development and Validation of the Interprofessional Collaboration Practice Competency Scale (IPCPCS) for Clinical Nurses.

Interprofessional collaborative practice is a core competency and is the key to strengthening health practice systems in order to deliver safe and high-quality nursing practice. However, there is no Interprofessional Collaboration Practice Competency Scale (IPCPCS) for clinical nurses in Taiwan. Therefore, the purposes of this study were to develop an IPCPCS and to verify its reliability and validity. This was a psychometric study with a cross-sectional survey using convenience sampling to recruit nurses from the seven hospitals of a medical foundation. A self-designed structured IPCPCS was rolled out via a Google survey. The data were analyzed using descriptive statistics, principal-axis factoring (PAF) with Promax rotation, Pearson correlation, reliability analysis, and one-way ANOVA. PAF analysis found that three factors could explain 77.76% of cumulative variance. These were collaborative leadership and interprofessional conflict resolution, interprofessional communication and team functioning, and role clarification and client-centered care. The internal consistency of the three factors (Cronbach's α) was between 0.970 to 0.978, and the Pearson correlation coefficients were between 0.814 to 0.883. Significant differences were presented in the IPCPCS score by age, education level, total years of work experience, position on the nursing clinical ladder, and participation in interprofessional education. In conclusion, the three factors used in the IPCPCS have good reliability and construct validity. This scale can be used as an evaluation tool of in-service interprofessional education courses for clinical nurses.

Assessing Frontal Lobe Function on Verbal Fluency and Emotion Recall in Autism Spectrum Disorder by fNIRS.

This study applied the functional near-infrared spectroscopy (fNIRS) to investigate frontal activity in autism when performing verbal fluency test and emotion recall task. We recruited 32 autistic adults without intellectual disability and 30 typically-developing controls (TDC). Prefrontal hemodynamic changes were evaluated by fNIRS when the participants performed the verbal fluency test and emotion recall task. fNIRS signals in the prefrontal cortex were compared between autism and TDC. Compared to TDC, autistic adults showed comparable performance on the verbal fluency test but exhibited lower frontal activity on the vegetable category. In the verbal fluency test, left frontal activity in TDC significantly increased in the vegetable category (vs. fruit category). In the emotion recall task, left frontal activity increased significantly in TDC when recalling emotional (vs. neutral) events. This increase of left frontal activity on the more difficult works was not found in autism. Similarly, brain activities were related to test performance only in TDC but not in autism. In addition, more severe social deficits were associated with lower frontal activity when recalling emotional events, independent of autism diagnosis. Findings suggested reduced frontal activity in autism, as compared to TDC, when performing verbal fluency tests. The reduction of left frontal activation in verbal fluency test and emotion recall tasks might reflect on the social deficits of the individual. The fNIRS may potentially be applied in assessing frontal lobe function in autism and social deficits in general population. Trial registration number: NCT04010409.

DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models.

Accurate classification of membrane proteins like ion channels and transporters is critical for elucidating cellular processes and drug development. We present DeepPLM_mCNN, a novel framework combining Pretrained Language Models (PLMs) and multi-window convolutional neural networks (mCNNs) for effective classification of membrane proteins into ion channels and ion transporters. Our approach extracts informative features from protein sequences by utilizing various PLMs, including TAPE, ProtT5_XL_U50, ESM-1b, ESM-2_480, and ESM-2_1280. These PLM-derived features are then input into a mCNN architecture to learn conserved motifs important for classification. When evaluated on ion transporters, our best performing model utilizing ProtT5 achieved 90% sensitivity, 95.8% specificity, and 95.4% overall accuracy. For ion channels, we obtained 88.3% sensitivity, 95.7% specificity, and 95.2% overall accuracy using ESM-1b features. Our proposed DeepPLM_mCNN framework demonstrates significant improvements over previous methods on unseen test data. This study illustrates the potential of combining PLMs and deep learning for accurate computational identification of membrane proteins from sequence data alone. Our findings have important implications for membrane protein research and drug development targeting ion channels and transporters. The data and source codes in this study are publicly available at the following link: https://github.com/s1129108/DeepPLM_mCNN.

Ribosomal quality control factors inhibit repeat-associated non-AUG translation from GC-rich repeats.

A GGGGCC (G4C2) hexanucleotide repeat expansion in C9ORF72 causes amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS/FTD), while a CGG trinucleotide repeat expansion in FMR1 leads to the neurodegenerative disorder Fragile X-associated tremor/ataxia syndrome (FXTAS). These GC-rich repeats form RNA secondary structures that support repeat-associated non-AUG (RAN) translation of toxic proteins that contribute to disease pathogenesis. Here we assessed whether these same repeats might trigger stalling and interfere with translational elongation. We find that depletion of ribosome-associated quality control (RQC) factors NEMF, LTN1 and ANKZF1 markedly boost RAN translation product accumulation from both G4C2 and CGG repeats while overexpression of these factors reduces RAN production in both reporter assays and C9ALS/FTD patient iPSC-derived neurons. We also detected partially made products from both G4C2 and CGG repeats whose abundance increased with RQC factor depletion. Repeat RNA sequence, rather than amino acid content, is central to the impact of RQC factor depletion on RAN translation-suggesting a role for RNA secondary structure in these processes. Together, these findings suggest that ribosomal stalling and RQC pathway activation during RAN translation inhibits the generation of toxic RAN products. We propose augmenting RQC activity as a therapeutic strategy in GC-rich repeat expansion disorders.

First Report of 'Candidatus Phytoplasma australasiaticum' Associated with Phyllody, Virescence, and Witches'-Broom Disease in Chrysanthemum morifolium in Taiwan.

Chrysanthemum morifolium (Asteraceae) is commonly grown as commercial cut flowers or pot mums worldwide. Common diseases of chrysanthemum include bacterial blight, fungal diseases, viruses, and phytoplasmas (Verma et al. 2003; Taloh et al. 2020). In June 2022, C. morifolium plants showing virescence, stunting, witches' broom, and phyllody symptoms were observed in 10 plants representing 10% of the estimated 100 plants in a field in Taichung City, Taiwan (Fig. S1). Three symptomatic samples along with three asymptomatic ones were collected for further study. Nested PCR was performed with two primer sets, P1/P7 (Deng and Hiruki 1991; Schneider et al. 1995) and R16F2n/R16R2 (Gundersen and Lee 1996) to amplify nearly full-length of 16S rDNA from the collected samples. The target 1.2-kb DNA band was only amplified from the symptomatic chrysanthemum plants. The amplicons were sequenced and a representative sequence deposited in GenBank under accession number OR501416. This sequence was used to search GenBank database by the Basic Local Alignment Search Tool (BLAST) program through the web service of National Center for Biotechnology Information (NCBI). In the 16S rDNA analyses, the three randomly picked amplicons from chrysanthemum phyllody phytoplasma (CPP) shared 100% identity with one another, and all shared 99.5% identity with the, 'Candidatus Phytoplasma australasiae' reference phytoplasma strain (Y10097). Further analysis using iPhyClassifier (Wei et al. 2007) revealed that CPP was most similar to the pattern of the peanut witches' broom phytoplasma in the 16SrII-A subgroup (GenBank Acc. No. L33765), with a pattern similarity coefficient of 1.0. For confirmation, the secY gene was amplified by secY-F/R primers (Li et al. 2014), the 1.2-kb band was sequenced and deposit in GenBank (Acc. No. OR508986). BLAST analysis showed that the secY sequence of CPP shared 99.93% of sequence identities to several 'Ca. P. australasiaticum' strains (MN543069, CP097312, CP120449, KC953013, MW085916, MW070030, CP040925). The phylogenetic tree analysis based on the secY gene by MEGA11 employing maximum-likelihood algorithm was performed and the bootstrap value was set as 1000 times for support of the stability for the clades. The result showed that CPP is closely related to other strains in 16SrII group (Fig. S2). Taken together, CPP is a 'Ca. P. australasiaticum' related-strain in 16SrII-A subgroup. This is the first report of chrysanthemum as a host of this phytoplasma in Taiwan, and might have an impact to the horticultural industry and the growers.

Engineering stable and non-immunogenic immunoenzymes for cancer therapy via in situ generated prodrugs.

Engineering human enzymes for therapeutic applications is attractive but introducing new amino acids may adversely affect enzyme stability and immunogenicity. Here we used a mammalian membrane-tethered screening system (ECSTASY) to evolve human lysosomal beta-glucuronidase (hBG) to hydrolyze a glucuronide metabolite (SN-38G) of the anticancer drug irinotecan (CPT-11). Three human beta-glucuronidase variants (hBG3, hBG10 and hBG19) with 3, 10 and 19 amino acid substitutions were identified that display up to 40-fold enhanced enzymatic activity, higher stability than E. coli beta-glucuronidase in human serum, and similar pharmacokinetics in mice as wild-type hBG. The hBG variants were two to three orders of magnitude less immunogenic than E. coli beta-glucuronidase in hBG transgenic mice. Intravenous administration of an immunoenzyme (hcc49-hBG10) targeting a sialyl-Tn tumor-associated antigen to mice bearing human colon xenografts significantly enhanced the anticancer activity of CPT-11 as measured by tumor suppression and mouse survival. Our results suggest that genetically-modified human enzymes represent a good alternative to microbially-derived enzymes for therapeutic applications.

Enhancing Hydrogen Evolution Catalysis through Potential-Induced Structural Phase Transition in Transition-Metal Dichalcogenide Thin Sheets.

Enhancing electrocatalytic performance relies on effective phase control, which influences key catalytic properties, such as chemical stability and electrical conductivity. Traditional methods for manipulating the phase of transition-metal dichalcogenides (TMDs), including high-temperature synthesis, Li intercalation, and doping, involve harsh conditions and energy-intensive processes. This study introduces an innovative approach to crafting heterophase structures (2H-1T-WS2) in TMDs, using WS2 as a model compound, encompassing both semiconducting (2H) and metallic (1T) types through a straightforward potential activation method. Insights from in situ electrochemical Raman spectroscopy, HR-TEM, and XPS measurements reveal distinctive partial phase-transition behavior. This behavior enables the partially exposed basal plane of 2H-1T-WS2 to demonstrate superior activity in the hydrogen evolution reaction (HER), attributed to enhanced electrical conductivity and the exposure of highly active sites. The potential-induced phase transition presents promising avenues for the development of catalysts with heterophase structures.

Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction.

Previous studies have reported a role of alterations in the brain's inhibitory control mechanism in addiction. Mounting evidence from neuroimaging studies indicates that its key components can be evaluated with brain oscillations and connectivity during inhibitory control. In this study, we developed an internet-related stop-signal task with electroencephalography (EEG) signal recorded to investigate inhibitory control. Healthy controls and participants with Internet addiction were recruited to participate in the internet-related stop-signal task with 19-channel EEG signal recording, and the corresponding event-related potentials and spectral perturbations were analyzed. Brain effective connections were also evaluated using direct directed transfer function. The results showed that, relative to the healthy controls, participants with Internet addiction had increased Stop-P3 during inhibitory control, suggesting that they have an altered neural mechanism in impulsive control. Furthermore, participants with Internet addiction showed increased low-frequency synchronization and decreased alpha and beta desynchronization in the middle and right frontal regions compared to healthy controls. Aberrant brain effective connectivity was also observed, with increased occipital-parietal and intra-occipital connections, as well as decreased frontal-paracentral connection in participants with Internet addiction. These results suggest that physiological signals are essential in future implementations of cognitive assessment of Internet addiction to further investigate the underlying mechanisms and effective biomarkers.

Exploring Inter-Brain Electroencephalogram Patterns for Social Cognitive Assessment During Jigsaw Puzzle Solving.

Social interaction enables the smooth progression of our daily lives. Mounting evidence from recent hyperscanning neuroimaging studies indicates that key components of social behavior can be evaluated using inter-brain oscillations and connectivity. However, mapping out inter-brain networks and developing neurocognitive theories that explain how humans co-create and share information during social interaction remains challenging. In this study, we developed a jigsaw puzzle-solving game with hyperscanning electroencephalography (EEG) signals recorded to investigate inter-brain activities during social interactions involving cooperation and competition. Participants were recruited and paired into dyads to participate in the multiplayer jigsaw puzzle game with 32-channel EEG signals recorded. The corresponding event-related potentials (ERPs), brain oscillations, and inter-brain functional connectivity were analyzed. The results showed different ERP morphologies of P3 patterns in competitive and cooperative contexts, and brain oscillations in the low-frequency band may be an indicator of social cognitive activities. Furthermore, increased inter-brain functional connectivity in the delta, theta, alpha, and beta frequency bands was observed in the competition mode compared to the cooperation mode. By presenting comparable and valid hyperscanning EEG results alongside those of previous studies using traditional paradigms, this study demonstrates the potential of utilizing hyperscanning techniques in real-life game-playing scenarios to quantitatively assess social cognitive interactions involving cooperation and competition. Our approach offers a promising platform with potential applications in the flexible assessment of psychiatric disorders related to social functioning.

MoCab: A Model Management System Based on FHIR for Clinical Decision Support.

MoCab is a framework that deploys high-accuracy medical models across various health information systems (HISs) using fast healthcare interoperability resources (FHIR). MoCab simplifies the process by importing and configuring stored models and retrieving data for prediction. Two case studies illustrate how MoCab can be used to support decision-making. The proposed framework increases model reusability across EHRs and improves the clinical decision-making process.

Self-Supervised Learning-Based General Laboratory Progress Pretrained Model for Cardiovascular Event Detection.

OBJECTIVE: Leveraging patient data through machine learning techniques in disease care offers a multitude of substantial benefits. Nonetheless, the inherent nature of patient data poses several challenges. Prevalent cases amass substantial longitudinal data owing to their patient volume and consistent follow-ups, however, longitudinal laboratory data are renowned for their irregularity, temporality, absenteeism, and sparsity; In contrast, recruitment for rare or specific cases is often constrained due to their limited patient size and episodic observations. This study employed self-supervised learning (SSL) to pretrain a generalized laboratory progress (GLP) model that captures the overall progression of six common laboratory markers in prevalent cardiovascular cases, with the intention of transferring this knowledge to aid in the detection of specific cardiovascular event. METHODS AND PROCEDURES: GLP implemented a two-stage training approach, leveraging the information embedded within interpolated data and amplify the performance of SSL. After GLP pretraining, it is transferred for target vessel revascularization (TVR) detection. RESULTS: The proposed two-stage training improved the performance of pure SSL, and the transferability of GLP exhibited distinctiveness. After GLP processing, the classification exhibited a notable enhancement, with averaged accuracy rising from 0.63 to 0.90. All evaluated metrics demonstrated substantial superiority ([Formula: see text]) compared to prior GLP processing. CONCLUSION: Our study effectively engages in translational engineering by transferring patient progression of cardiovascular laboratory parameters from one patient group to another, transcending the limitations of data availability. The transferability of disease progression optimized the strategies of examinations and treatments, and improves patient prognosis while using commonly available laboratory parameters. The potential for expanding this approach to encompass other diseases holds great promise. CLINICAL IMPACT: Our study effectively transposes patient progression from one cohort to another, surpassing the constraints of episodic observation. The transferability of disease progression contributed to cardiovascular event assessment.

Maintenance of species boundaries amid hybridization in two island gingers with similar ecological niches.

Understanding species boundaries maintenance in the face of hybridization/introgression is an intriguing yet complex topic in evolutionary biology. The underlying mechanisms, however, remain elusive. To address this, we propose to investigate the role of climatic shifts in shaping genetic structure and influencing species boundaries. We combine multilocus genetic data and species distribution modeling to explore how past and current climatic shifts affect the genetic structure and demographic history of two Taiwan endemic gingers, Zingiber pleiostachyum and Z. shuanglongense. We identified a well-delimited genetic structure with evidence of admixture, indicating incomplete reproductive isolation between the two gingers. This is likely due to secondary contact and range overlap during the last glacial maximum, leading to sporadic instances of hybridization. Niche overlap tests based on climate and soil data indicate that these two gingers occupy similar but nonidentical ecological niches. Furthermore, we found that the considerable differences in their current geographic distribution and altitude preferences might have resulted from different seed dispersal capabilities and competitive exclusion due to their similar niche preferences. Our results reveal a model where altitudinal differentiation and dispersal strategy synergistically reinforce the species divergence, thereby illuminating the importance of these factors in shaping and maintaining the island's biodiversity.

Altered Inhibitory Control Mechanism of Internet Addiction: An Electroencephalogram Study of Brain Oscillations and Connectivity.

The development of the Internet has changed people's lives and has resulted in a new type of addictive behavior. In the past decade, Internet game addiction has been identified as a mental illness. Considering internet game addiction as the only cause of mental illness is limited in its view, as internet games, social platforms and other internet multimedia are also widely used. Thus, other internet-related behaviors, that maybe addictive, should also be included. Previous neuroimaging studies have reported a role of alteration in brain's inhibitory control mechanism in addiction. However, the results are still diverse with inconsistent findings. In this study, we used an Internet-related stop signal task with EEG signals recorded to study the relationship between internet addiction through brain oscillations and functional connectivity. We also compared the differences in the brain connectivity between addicted and non-addicted participants using phase lag index. We found that the brain connectivity in participants addicted to the internet is significantly greater than that of nonaddicted users.Clinical Relevance- In this study, we assessed brain functional networks of participants with Internet Gaming Disorder and internet addiction.

Social Brain Activation and Connectivity in Autism Spectrum Disorders: An Electroencephalogram Study of Jigsaw Puzzle Solving.

Autism spectrum disorder requires early detection and treatment. Thus, we developed a method to obtain reliable neurophysiological biomarkers to assist in diagnosing autism. This method includes a simple but typical jigsaw puzzle that allows participants to play and interact with each other. While playing this game, brain signals of the participants were observed and analyzed. The patients with autism were found to have differences in the time range of some event-related potential, such as P300 and N400. Altered patterns of function connectivity were also found in delta frequency bands in the patients while interacting with other people. Working around patients' capabilities, the jigsaw puzzle game was designed as easy to complete; this caused fewer mismatch conditions. The result suggested that these patterns are promising neurophysiological biomarker to assist doctors in social cognitive assessment in autism.Clinical Relevance-This study demonstrated the possibility of using hyperscanning technique for social cognitive assessment of autism spectrum disorder.