Introducing Triplex Forming Oligonucleotide into Loop-Mediated Isothermal Amplification for Developing a Lateral Flow Biosensor for Streptococci Detection.

Loop-mediated isothermal amplification (LAMP) technology is extensively utilized for the detection of infectious diseases owing to its rapid processing and high sensitivity. Nevertheless, conventional LAMP signaling methods frequently suffer from a lack of sequence specificity. This study integrates a triplex-forming oligonucleotide (TFO) probe into the LAMP process to enhance sequence specificity. This TFO-LAMP technique was applied for the detection of Group B Streptococcus (GBS). The TFO probe is designed to recognize a specific DNA sequence, termed the TFO targeting sequence (TTS), within the amplified product, facilitating detection via fluorescent instrumentation or lateral flow biosensors. A screening method was developed to identify TFO sequences with high affinity to integrate TFO into LAMP, subsequently incorporating a selected TTS into an LAMP primer. In the TFO-LAMP assay, a FAM-labeled TFO is added to target the TTS. This TFO can be captured by an anti-FAM antibody on lateral flow test strips, thus creating a nucleic acid testing biosensor. The efficacy of the TFO-LAMP assay was confirmed through experiments with specimens spiked with varying concentrations of GBS, demonstrating 85% sensitivity at 300 copies and 100% sensitivity at 30,000 copies. In conclusion, this study has successfully developed a TFO-LAMP technology that offers applicability in lateral flow biosensors and potentially other biosensor platforms.

Survival-related genes are diversified across cancers but generally enriched in cancer hallmark pathways.

BACKGROUND: Pan-cancer studies have disclosed many commonalities and differences in mutations, copy number variations, and gene expression alterations among cancers. Some of these features are significantly associated with clinical outcomes, and many prognosis-predictive biomarkers or biosignatures have been proposed for specific cancer types. Here, we systematically explored the biological functions and the distribution of survival-related genes (SRGs) across cancers. RESULTS: We carried out two different statistical survival models on the mRNA expression profiles in 33 cancer types from TCGA. We identified SRGs in each cancer type based on the Cox proportional hazards model and the log-rank test. We found a large difference in the number of SRGs among different cancer types, and most of the identified SRGs were specific to a particular cancer type. While these SRGs were unique to each cancer type, they were found mostly enriched in cancer hallmark pathways, e.g., cell proliferation, cell differentiation, DNA metabolism, and RNA metabolism. We also analyzed the association between cancer driver genes and SRGs and did not find significant over-representation amongst most cancers. CONCLUSIONS: In summary, our work identified all the SRGs for 33 cancer types from TCGA. In addition, the pan-cancer analysis revealed the similarities and the differences in the biological functions of SRGs across cancers. Given the potential of SRGs in clinical utility, our results can serve as a resource for basic research and biotech applications.

TACCO, a Database Connecting Transcriptome Alterations, Pathway Alterations and Clinical Outcomes in Cancers.

Because of innumerable cancer sequencing projects, abundant transcriptome expression profiles together with survival data are available from the same patients. Although some expression signatures for prognosis or pathologic staging have been identified from these data, systematically discovering such kind of expression signatures remains a challenge. To address this, we developed TACCO (Transcriptome Alterations in CanCer Omnibus), a database for identifying differentially expressed genes and altered pathways in cancer. TACCO also reveals miRNA cooperative regulations and supports construction of models for prognosis. The resulting signatures have great potential for patient stratification and treatment decision-making in future clinical applications. TACCO is freely available at http://tacco.life.nctu.edu.tw/ .

Lessons from the Largest Epidemic of Avian Influenza Viruses in Taiwan, 2015.

The largest epidemic of avian influenza (AI) in history attacked poultry and wild birds throughout Taiwan starting January 6, 2015. This study analyzed surveillance results, epidemiologic characteristics, and viral sequences by using government-released information, with the intention to provide recommendations to minimize future pandemic influenza. The H5 clade 2.3.4.4 highly pathogenic AI viruses (HPAIVs) had not been detected in Taiwan before 2015. During this epidemic, four types of etiologic agents were identified: the three novel subtypes H5N2, H5N8, and H5N3 clade 2.3.4.4 HPAIVs and one endemic chicken H5N2 subtype (Mexican-like lineage) of low pathogenic AI viruses. Cocirculation of mixed subtypes also occurred, with H5N2 clade 2.3.4.4 HPAIVs accompanied by the H5N8 and H5N3 subtypes or old H5N2 viruses in the same farm. More than 90% of domestic geese died from this AI epidemic; geese were affected the most at the early outbreaks. The epidemic peaked in mid-January for all three novel H5 subtypes. Spatial epidemiology found that most affected areas were located in southwestern coastal areas. In terrestrial poultry (mostly chickens), different geographic distributions of AI virus subtypes were detected, with hot spots of H5N2 clade 2.3.4.4 vs. past-endemic old H5N2 viruses in Changhwa (P = 0.03) and Yunlin (P = 0.007) counties, respectively, of central Taiwan. Phylogenetic and sequence analyses of all the early 10 Taiwan H5 clade 2.3.4.4 isolates covering the three subtypes showed that they were very different from the HA of the past local H5 viruses from domestic ducks (75%-80%) and chickens (70%-75%). However, they had the highest sequence identity percentages (99.53%-100%), with the HA of A/crane/Kagoshima/KU13/2014(H5N8) isolated on December 7, 2014, in Japan being higher than those of recent American and Korean H5 HPAIVs [A/Northern pintail/Washington/40964/2014 (H5N2) and A/gyrfalcon/Washington/41088-6/2014 (H5N8): 99.02%-99.54% and A/Baikal teal/Korea/Donglim3/2014 (H5N8): 98.61%-99.08%], implying a likely common ancestor of these H5 clade 2.3.4.4 viruses. The multiple subtypes of H5 clade 2.3.4.4 HPAIVs imply high viral reassortment. We recommend establishing an integrated surveillance system, involving clinical, virologic, and serologic surveillance in poultry and wild birds, swine and other mammals prevalent on multiple-animal mixed-type traditional farms, and high-risk human populations, as a crucially important step to minimize future pandemic influenza.

Emergence of a Fermionic Finite-Temperature Critical Point in a Kondo Lattice.

The underlying Dirac point is central to the profound physics manifested in a wide class of materials. However, it is often difficult to drive a system with Dirac points across the massless fermionic critical point. Here by exploiting screening of local moments under spin-orbit interactions in a Kondo lattice, we show that below the Kondo temperature, the Kondo lattice undergoes a topological transition from a strong topological insulator to a weak topological insulator at a finite temperature T_{D}. At T_{D}, massless Dirac points emerge and the Kondo lattice becomes a Dirac semimetal. Our analysis indicates that the emergent relativistic symmetry dictates nontrivial thermal responses over large parameter and temperature regimes. In particular, it yields critical scaling behaviors both in magnetic and transport responses near T_{D}.