Emerging trends for radioimmunotherapy in solid tumors.

Due to its ability to target both known and occult lesions, radioimmunotherapy (RIT) is an attractive therapeutic modality for solid tumors. Poor tumor uptake and undesirable pharmacokinetics, however, have precluded the administration of radioimmunoconjugates at therapeutically relevant doses thereby limiting the clinical utility of RIT. In solid tumors, efficacy of RIT is further compromised by heterogeneities in blood flow, tumor stroma, expression of target antigens and radioresistance. As a result significant efforts have been invested toward developing strategies to overcome these impediments. Further, there is an emerging interest in exploiting short-range, high energy α-particle emitting radionuclides for the eradication of minimal residual and micrometastatic disease. As a result several modalities for localized therapy and models of minimal disease have been developed for preclinical evaluation. This review provides a brief update on the recent efforts toward improving the efficacy of RIT for solid tumors, and development of RIT strategies for minimal disease associated with solid tumors. Further, some of promising approaches to improve tumor targeting, which showed promise in the past, but have now been ignored are also discussed

Validation of the simulations by the High-resolution Operational Ocean Forecast and reanalysis System (HOOFS) for the Bay of Bengal

In this report, we present a detailed comparison and validation of the simulations from high-resolution (1/480) ocean circulation model for the Bay of Bengal (BBHOOFS) using Regional Ocean Modeling System (ROMS) with the available ocean observations and the simulations by the relatively lower resolution (1/120) basinscale general circulation model setup (IO-HOOFS), which is resently used to provide ocean forecasts for the Bay of Bengal. Comparison of vertical profiles of currents, temperature, Sea Level Anomaly (SLA) and Sea Surface Temperature (SST) for both model setups are carried for the period of 2013-2014. Comparison of the circulation features in the shelf and slope regions off the east coast of India simulated by the model with the ADCP observations shows that simulations by the BB-HOOFS are superior in terms of its ability to capture the features and variability in different space and time scales. In addition, simulations of currents by BB-HOOFS show high correlation and low RMSE values in the northern part of the shelf and slope off the east coast of India compared to south. Comparison of temperature simulations by the two model setups with observation shows that the simulations of BB-HOOFS is better, with high correlation and low RMSE values especially in the thermocline regions, compared to IO-HOOFS. However, comparison of SST and SLA simulated by BB-HOOFS with the satellite based observations is not showing any significant improvement compared to the imulations by IO-HOOFS

What controls seasonal evolution of sea surface temperature in the Bay of Bengal? Mixed layer heat budget analysis using moored buoy observations along 90°E

Author Posting. © The Oceanography Society, 2016. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 29, no. 2 (2016): 202–213, doi:10.5670/oceanog.2016.52.Continuous time-series measurements of near surface meteorological and ocean variables obtained from Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) moorings at 15°N, 90°E; 12°N, 90°E; and 8°N, 90°E and an Ocean Moored buoy Network for Northern Indian Ocean (OMNI) mooring at 18°N, 90°E are used to improve understanding of air-sea interaction processes and mixed layer (ML) temperature variability in the Bay of Bengal (BoB) at seasonal time scales. Consistent with earlier studies, this analysis reveals that net surface heat flux primarily controls the ML heat balance. The penetrative component of shortwave radiation plays a crucial role in the ML heat budget in the BoB, especially during the spring warming phase when the ML is thin. During winter and summer, vertical processes contribute significantly to the ML heat budget. During winter, the presence of a strong barrier layer and a temperature inversion (warmer water below the ML) leads to warming of the ML by entrainment of warm subsurface water into the ML. During summer, the barrier layer is relatively weak, and the ML is warmer than the underlying water (i.e., no temperature inversion); hence, the entrainment cools the mixed layer. The contribution of horizontal advection to the ML heat budget is greatest during winter when it serves to warm the upper ocean. In general, the residual term in the ML heat budget equation is quite large during the ML cooling phase compared to the warming phase when the contribution from vertical heat flux is small.WHOI buoy deployment was supported by the US Office of Naval Research (grant no. N00014- 13-10453)

Precipitation event detection based on air temperature over the Equatorial Indian Ocean

Air temperature (AT) and precipitation observations obtained from RAMA (Research Moored Array for African-Asian-Australian Monsoon Analysis and prediction) buoy at 0° N, 90° E from July 2009 to June 2017 are used to identify rainfall events. Based on the Random forest method, which consists of classification and regression based on decision trees, an algorithm is developed to identify the rainfall events from the change in AT data with high accuracy. During the study period, a total of 22461 abrupt drops in air-temperature events were identified by the algorithm. Around 75 % of these events were used to train and develop the clustering algorithm, and the rest of the events were used for validation with the precipitation data available from the buoy. The algorithm can identify more than 94 % of rain events accurately when the classification is binary. When the rain events are classified similar to the India Meteorological Department's classification, the algorithm is still able to identify the rain events; however, the performance degrades to ~ 84 % accuracy

Unbiased analysis of pancreatic cancer radiation resistance reveals cholesterol biosynthesis as a novel target for radiosensitisation.

BACKGROUND: Despite its promise as a highly useful therapy for pancreatic cancer (PC), the addition of external beam radiation therapy to PC treatment has shown varying success in clinical trials. Understanding PC radioresistance and discovery of methods to sensitise PC to radiation will increase patient survival and improve quality of life. In this study, we identified PC radioresistance-associated pathways using global, unbiased techniques. METHODS: Radioresistant cells were generated by sequential irradiation and recovery, and global genome cDNA microarray analysis was performed to identify differentially expressed genes in radiosensitive and radioresistant cells. Ingenuity pathway analysis was performed to discover cellular pathways and functions associated with differential radioresponse and identify potential small-molecule inhibitors for radiosensitisation. The expression of FDPS, one of the most differentially expressed genes, was determined in human PC tissues by IHC and the impact of its pharmacological inhibition with zoledronic acid (ZOL, Zometa) on radiosensitivity was determined by colony-forming assays. The radiosensitising effect of Zol in vivo was determined using allograft transplantation mouse model. RESULTS: Microarray analysis indicated that 11 genes (FDPS, ACAT2, AG2, CLDN7, DHCR7, ELFN2, FASN, SC4MOL, SIX6, SLC12A2, and SQLE) were consistently associated with radioresistance in the cell lines, a majority of which are involved in cholesterol biosynthesis. We demonstrated that knockdown of farnesyl diphosphate synthase (FDPS), a branchpoint enzyme of the cholesterol synthesis pathway, radiosensitised PC cells. FDPS was significantly overexpressed in human PC tumour tissues compared with healthy pancreas samples. Also, pharmacologic inhibition of FDPS by ZOL radiosensitised PC cell lines, with a radiation enhancement ratio between 1.26 and 1.5. Further, ZOL treatment resulted in radiosensitisation of PC tumours in an allograft mouse model. CONCLUSIONS: Unbiased pathway analysis of radioresistance allowed for the discovery of novel pathways associated with resistance to ionising radiation in PC. Specifically, our analysis indicates the importance of the cholesterol synthesis pathway in PC radioresistance. Further, a novel radiosensitiser, ZOL, showed promising results and warrants further study into the universality of these findings in PC, as well as the true potential of this drug as a clinical radiosensitiser

INCOIS-Real time Automatic Weather Station(IRAWS) dataset - Quality control and significance of height correction

The INCOIS-Real time Automatic Weather Station(IRAWS) program was started in the year 2009 and was first installed onboard ORV Sagar Nidhi. Currently, there are 36 ships carrying IRAWS setup. Apart from storing one minute observations in the log onboard the ship, hourly averaged observations are reported through INSAT satellite communication. This report briefs about the hourly dataset of IRAWS and its quality control. In this report, QC results of SST and all meteorological parameters except radiation parameters is discussed. Specific quality check was applied to wind speed (WS) and sea surface temperature (SST) observations. The WS observations measured onboard few ships had a dimensional correction and SST was observed only on few ships. As SST observations are required to compute meteorological variables like DBT, RH, WS to standard height of 10 m, level-3 dataset of AVHRR SST was utilized in place of IRAWS SST wherever the data is found to be faulty. On similar terms bias correction could not be applied to IRAWS SST with the help of AVHRR SST as the error in SST observations are due to the failure of sensor. However all those IRAWS SST observations that passed the QC check were observed to be of high quality and have a correlation coefficient of 0.5 with AVHRR SST and is significant at 95% significant level. Apart from SST and radiation observations, all other parameters observations are found out to be of good quality with 70 to 90 QC pass percentage . Apart from the details of QC check, significance of representing climate variable at a homogeneous standard height is also shown in this repor

Quantifying tropical cyclone's effect on the biogeochemical processes using profiling float observations in the Bay of Bengal

Physical and biogeochemical observations from an autonomous profiling Argo float in the Bay of Bengal show significant changes in upper ocean structure during the passage of Tropical Cyclone (TC) Hudhud (7–14 October 2014). TC Hudhud mixed water from a depth of about 50 m into the surface layers through a combination of upwelling and turbulent mixing. Mixing was extended into the depth of nutricline, the oxycline and the subsurface‐chlorophyll‐maximum; thus had a strong impact on the biogeochemistry of the upper ocean. Before the storm, the near‐surface layer was nutrient depleted and was thus oligotrophic with the chlorophyll‐a concentration of less than 0.15 mg m‐3. Storm mixing initially increased the chlorophyll by 1.4 mg m‐3, increased the surface nitrate concentration to about 6.6 μM kg‐1, and decreased the sub‐surface dissolved oxygen (30–35 m) to 31 % of saturation (140 μM). These conditions were favorable for phytoplankton growth resulting in an estimated increase in primary productivity averaging 1.5 g C m‐2 day‐1 over 15 days. During this bloom, chlorophyll‐a increased by 3.6 mg m‐3, and dissolved oxygen increased from 111 % to 123 % of saturation. Similar observations during TC Vardah (6–12 December 2016) showed much less mixing. Our analysis suggests that relatively small (high) translation speed and presence of cold (warm) core eddy leads to strong (weak) oceanic response during TC Hudhud (TC Vardah). Thus, although cyclones can cause strong biogeochemical responses in the Bay of Bengal, the strength of response depends on the properties of the storm and the prevailing upper ocean structure such as presence of mesoscale eddies

Resolving orographic rainfall on the Indian West coast

We discuss a method to obtain the spatial estimates of rainfall on the Indian west coast for calculating the surface water budget. The region includes the basin of the Mandovi River, a typical west-coast river whose catchment area includes the Sahyadris range. The rainfall maps obtained by a multivariate interpolation scheme, with elevation as the third variable, were able to capture the sharp increase in rainfall on the windward slopes and the exponential decay in rainfall on the leeward side. The rainfall maps were used to force a hydrological model and the simulated discharge was within 16% of the observed discharge in 16 of 18 years during 1981-1998; the average error over the 18 years was 8%, which is much less than the estimated error of ~15-20% in the observed discharge. The Mandovi river discharge provided a reliable and independent validation of the accuracy of the rainfall estimate as the river is purely rain-fed. The method provides a better estimate of rainfall in the Mandovi basin, and therefore for the Indian west coast, than existing rainfall datasets. The key result is that treating the windward and leeward sides separately by an a priori, subjective extraction of the ridge line can reduce the underestimation of rainfall that is common in mountainous terrain when the data coverage is sparse