Papua is one of part in Indonesia which is the geology research of that place isn’t developed and limited. It causes the seismotectonic of Papua hasn’t been known. WinITDB was used to determine the dip angle plate which was on the north part of Papua. The determination of angle was done through seismicity’s cross section analysis in the area. To show that seismicity, earthquake history data that ever occurred in the area is needed. The result on the seismicity’s cross section of plane A–A’, was confluence by two plates with angle 150° against horizontal on the depth up to ±68 km. On the seismicity’s cross section of plane B–B’ had angle 135° against horizontal on the ±82 km depth. On the plane C–C’ seismicity’s cross section, was confluence of two plate which located between -1,77°S until -4,97°S subducted until 171 km depth on 1,38°N - 4,97°S. It proved that subduction characteristic in the northern Papua which was Australia continent plate subducted to north, followed by collision and the Pacific plate subduction on New Guinea. It is also confirmed by focus mechanism analysis which showed the earthquake activities are controlled by the not really deep active fault.

The diel variations of viruses (< 0.2 μm), picoplankton (0.2—2 μm; heterotrophic bacteria, Syn-echococcus spp., Prochlorococcus spp. and picoeukaryotes) and nanoplankton (2—20 μm; hetero-trophic nanoflagellates and pigmented nanoflagellates) were investigated for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. A period of wind change associated with rain and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. The abundance of bacteria did not follow a consistent diel pattern, while viral abundance positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nano-flagellate grazing could control their abundances and may explain temporally varying picocyanobacteria abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

We used flow cytometry to follow diel variations of viruses, picoplankton, and nanoflagellates for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. An event of wind change, associated with rainfall and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. We observed that bacterial abundance did not follow a consistent diel pattern and that viral abundance was positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nanoflagellate grazing could control their abundances and may explain temporally varying picocyanobacterial abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

The presence of anti SARS-CoV2-RBD antibody (Anti-RBD) prevents severe COVID-19. We aimed to determine the accuracy of a point-of-care Anti-RBD test implemented in person living with HIV (PLWH), systemic lupus erythematosus (SLE), and chronic kidney disease (CKD). We enrolled 182 non-comorbid subjects and 335 persons with comorbid (PLWH, SLE, CKD) to test anti-RBD assay compared to surrogate viral neutralization (SVNT) as the reference test. We performed linear correlation analysis between anti-RBD vs SVNT and a ROC analyses to ascertain anti-RBD cut-off at 30%, 60%, and 90% inhibition of SVNT to calculate accuracy. Correlations of anti-RBD to SVNT among all groups were excellent with R= 0.7903, R=0.7843, R=0.8153 among non-comorbid, SLE and CKD groups, respectively, with significantly higher correlation among the PLWH group (R=0.8877; p-value=0.0072) compared to non-comorbid group. The accuracy of the anti-RBD test among PLWH and CKD group was similar with the non-comorbid but showed lower sensitivity in the SLE group (p=0.000014). The specificity of the test remained high in all groups. In conclusion, the Anti-RBD test had excellent correlation to SVNT. The persistently high specificity in all groups suggests that this test can be reliably utilized to detect presence of low neutralization capacity, prompting additional vaccination.