Reliability based design rules for column buckling

A load factor design criterion based on a first-order probability theory is derived for the buckling strength of structural steel columns. The load factors and strength factor are evaluated using available information and testresults. It is also shown how different column theories can be compared on the basis of design resistance obtained from each theory. The paper concludes by describing how probabilistic problems can be simplified by using a first order theory.     

An algorithm for hidden line ruled surface display using microprocessor

A simple algorithm for hidden line Ruled Surface graphics, typically used in Radio Astronomy is discussed using low cost microcomputer system built around Motorola 6800 processor and Matrox 256**2 graphics module of raster size 256 × 256 points. Resolution of the plot can be improved by displaying on a bigger raster like 1024 × 1024 points.     

The Structures of Gd(III) Chelates Conjugated at the Periphery of 3-(1’-Hexyloxy)ethyl-3-devinylpyropheophorbide-a (HPPH) Have a Significant Impact on the Imaging and Therapy of Cancer

3-(1’-Hexyloxyethyl)-3-devinyl-pyropheophorbide-a (HPPH or Photochlor), a tumor-avid chlorophyll-a derivative currently undergoing human clinical trials, was conjugated at various peripheral positions (position-17 or 20) of HPPH with either Gd(III)-aminobenzyl-DTPA (Gd(III) DTPA) or Gd(III)-aminoethylamido-DOTA (Gd(III) DOTA). The corresponding conjugates were evaluated for in vitro PDT efficacy, T₁, T₂ relaxivities, in vivo fluorescence, and MR imaging under similar treatment parameters. Among these analogs, the water-soluble Gd(III)-aminoethylamido-DOTA linked at position-17 of HPPH, i. e., HPPH-17-Gd(III) DOTA, demonstrated strong potential for tumor imaging by both MR and fluorescence, while maintaining the PDT efficacy in BALB/c mice bearing Colon-26 tumors (7/10 mice were tumor free on day 60). In contrast to Gd(III) DTPA (Magnevist) and Gd(III) DOTA (Dotarem), the HPPH-Gd(III) DOTA retains in the tumor for a long period of time (24 to 48 h) and provides an option of fluorescence-guided cancer therapy. Thus, a single agent can be used for cancer-imaging and therapy. However, further detailed pharmacokinetic, pharmacodynamic, and toxicological studies of the conjugate are required before initiating Phase I human clinical trials.     

A Pyropheophorbide Analogue Containing a Fused Methoxy Cyclohexenone Ring System Shows Promising Cancer-Imaging Ability

Herein we report the synthesis, photophysical properties, positron emission tomography (PET) imaging and photodynamic therapy (PDT) efficacy of methyl 3-(1′-m-iodobenzyloxy)ethyl-3-devinyl-verdin 4 (with or without the ¹²⁴I isotope). The PET imaging ability and ex vivo biodistribution of [¹²⁴I] 4 were compared with the well-studied methyl [3-(¹²⁴1′-m-iodobenzyloxy)ethyl]-3-devinyl-pyropheophorbide-a methyl ester (PET-ONCO or [¹²⁴I] 2 ) and [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) in BALB/c mice bearing colon-26 tumors. Whole-body PET images of [¹²⁴I] 4 containing a fused methoxy cyclohexenone ring system showed excellent tumor contrast with time (72>48>24 h post-injection). Ex vivo biodistribution results indicate that relative to the current clinical standard [¹⁸F]FDG and [¹²⁴I] 2 in 2 % ethanol formulation, [¹²⁴I] 4 , at the same radioactive dose (25 μCi per mouse), showed higher tumor uptake at 24 h post-injection and longer tumor retention. In biological environments, compound 4 showed lower fluorescence and lower singlet oxygen yield than 2 , which is possibly due to higher aggregation caused by the presence of a fused cyclohexenone ring system, resulting in limited in vitro/in vivo PDT efficacy. Therefore, the chlorophyll-a analogue [¹²⁴I] 4 provides easy access to a novel PET imaging agent (with no skin phototoxicity) to image cancer types—brain, renal carcinomas, pancreas—in which [¹⁸F]FDG shows limitations.     

Solid lipid nanoparticles of Annona muricata fruit extract: formulation,optimization and in vitro cytotoxicity studies

The present study was aimed to develop Annona muricata fruit extract loaded solid lipid nanoparticles (SLNs) and explore its cytotoxic potential in vitro model of breast cancers. Extract loaded SLNs were successfully prepared by high-pressure homogenization followed by ultrasonication method and optimized using 2³ full factorial design. The extract loaded SLNs were characterized using different parameters such as particle size (PS), % entrapment efficiency (EE), zeta potential (ZP) and % cumulative drug release (CDR). The SLNs formulation was optimized on the basis of software analysis with an overall desirability factor. The PS and %EE of the optimized formulation were found to be 134.8?nm and 83.26%, respectively. The optimized formulation showed a CDR of 79.83% up to 48?h. In vitro cytotoxicity efficacy of extract loaded SLNs was determined using MTT and Apoptosis assay and compared to that of a free extract. The SLNs showed a notable apoptotic effect and better efficacy to kill MCF7 cancer cells as compared to free extract. Thus, extract loaded SLNs could be an alternative dosage form which possibly controls therapeutic action with reducing side effect.     

Potato starch-assisted green synthesis of nanoferrite and ferrite–semiconductor nanocomposites for effective visible light photocatalytic degradation of methylene blue

Journal of Materials Science - Biodegradable potato starch-assisted nanoferrite and ferrite–semiconductor nanocomposites have been synthesized by the co-precipitation method for the...     

Scrap leather valorization through composite fabrication using mustard oil resin and N-vinyl-2-pyrrolidone

Iranian Polymer Journal - Composites derived from petroleum sources like epoxy, unsaturated polyester and phenolics have limitations due to non-biodegradability toxicity which have harmful effects...     

Modeling and simulation of temperature drift for ISFET-based pH sensor and its compensation through machine learning techniques

The paper presents modeling and simulation of ion-sensitive field-effect transistor (ISFET)-based pH sensor with temperature-dependent behavioral macromodel and proposes to compensate the temperature drift in the sensor using intelligent machine learning (ML) models. The macromodel is built using SPICE by introducing electrochemical parameters in a metal-oxide-semiconductor field-effect transistor (MOSFET) model to simulate ISFET characteristics. We account for the temperature dependence of electrochemical and semiconductor parameters in our macromodel to increase its robustness. The macromodel is then exported as a subcircuit element, which is used to design the readout interface circuit. A simple constant-voltage, constant-current (CVCC) topology is utilized to generate the data for temperature drift in ISFET pH sensor, which is used to train and test state-of-the-art ML-based regression models in order to compensate the drift behavior. The experimental results demonstrate that the random forest (RF) technique achieves the best performance with very high correlation and low error rate. Corresponding curves for output signal using the trained models show highly temperature-independent characteristics when tested for pH 2, 4, 7, 10, and 12, and we obtained a root mean squared error (RMS) variation of ΔpH ≤ 0.024 over a temperature range of 15°C to 55°C in comparison with ΔpH ≤ 1.346 for uncompensated output signal. This work establishes the framework for integration of ML techniques for drift compensation of ISFET chemical sensor to improve its performance.