Proof-of-Concept Study of Using Supervised Machine Learning Algorithms to Predict Self-Care and Glycemic Control in Type 1 Diabetes Patients on Insulin Pump Therapy

ObjectiveUsing supervised machine learning algorithms (SMLAs), we built models to predict the probability of type 1 diabetes mellitus patients on insulin pump therapy for meeting insulin pump self-management behavioral (IPSMB) criteria and achieving good glycemic response within 6 months.MethodsThis was a single-center retrospective chart review of 100 adult type 1 diabetes mellitus patients on insulin pump therapy (≥6 months). Three SMLAs were deployed: multivariable logistic regression (LR), random forest (RF), and K-nearest neighbor (k-NN); validated using repeated three-fold cross-validation. Performance metrics included area under the curve-Receiver of characteristics for discrimination and Brier scores for calibration.ResultsVariables predictive of adherence with IPSMB criteria were baseline hemoglobin A1c, continuous glucose monitoring, and sex. The models had comparable discriminatory power (LR = 0.74; RF = 0.74; k-NN = 0.72), with the RF model showing better calibration (Brier = 0.151). Predictors of the good glycemic response included baseline hemoglobin A1c, entering carbohydrates, and following the recommended bolus dose, with models comparable in discriminatory power (LR = 0.81, RF = 0.80, k-NN = 0.78) but the RF model being better calibrated (Brier = 0.099).ConclusionThese proof-of-concept analyses demonstrate the feasibility of using SMLAs to develop clinically relevant predictive models of adherence with IPSMB criteria and glycemic control within 6 months. Subject to further study, nonlinear prediction models may perform better.     

Cambrian Acritarchs from the Col di Foglia (Agordo) southalpine metamorphic basement, Italian Eastern Alps: the oldest biostratigraphic record in the alps

Abstract  The Lower Palaeozoic biostratigraphic records in the Alps are briefly reviewed and the result of a new study of the acritarch assemblage found by Sassi et al. (1984) in the greenschist facies black metapelites of the Southalpine metamorphic basement at Col di Foglia, and studied by Kalvacheva et al. (1986), is presented. The new  taxonomic and biostratigraphic study indicates a late Cambrian age, which is the oldest unquestionable, recently assessed, biostratigraphic dating of the entire Alps, as well as of the Italian peninsular. Keywords Alps, Southalpine metamorphic basement, Eastern Alps, Agordo, Acritarchs, Cambrian Subject codes: G17002     

Association between the XRCC3 polymorphisms and breast cancer risk: meta-analysis based on case–control studies

The previous published data on the association between X-ray repair cross-complementing group 3 (XRCC3) T241M, A4541G, and A17893G polymorphisms and breast cancer risk remained controversial. Hence, we performed a meta-analysis to investigate the association between breast cancer and XRCC3 T241M (21,910 cases and 23,961 controls), A4541G (9,633 cases and 10,994 controls), and A17893G polymorphisms (10,761 cases and 12,235 controls) in different inheritance models. When all the eligible studies were pooled into the meta-analysis of XRCC3 T241M polymorphism, significantly increased risk of breast cancer was observed in recessive model (odds' ratio [OR] = 1.10, 95% confidence interval [CI] = 1.04–1.16) and in additive model (OR = 1.10, 95% CI = 1.03–1.16). No significant association was found between A4541G polymorphism and breast cancer risk. When all the eligible studies were pooled into the meta-analysis of XRCC3 A17893G polymorphism, no significant association was found in any genetic model. Additionally, when one study was deleted in the sensitive analysis, the results of XRCC3 A17893G were changed in the additive model (OR = 0.90, 95% CI = 0.82–0.99) and dominant model (OR = 0.94, 95% CI = 0.89–0.99). In summary, this meta-analysis indicates that T241M polymorphism show an increased breast cancer risk and A17893G polymorphism may be associated with decreased breast cancer risk. A study with the larger sample size is needed to further evaluated gene-environment interaction on XRCC3 T241M, A4541G, and A17893G polymorphisms and breast cancer risk.     

The state and the future of the Earth, planetary and environmental sciences, especially in Italy

Abstract  A critical review of the health state of the Earth sciences is carried out for the world and for Italy, with special regard to both their traditional branches and those recently developed to address the preservation of the Italian environment and cultural heritage. Past and recent achievements by Lincei members who contributed to the progress of the Earth sciences vision to changing public opinion on the impact of natural and human actions on the environment are briefly discussed. The possible contribution of renovated “Rendiconti Lincei” to distributing internationally the present best achievements by Italian Earth scientists and by foreign scientists working on Italian soil is also analyzed. Keywords Geology, Mineralogy, Palaeontology, Applied Geosciences, Cultural Heritage Subject codes: U12007, G17002, G24009     

A genetic variant at KIF1B predicts clinical outcome of HBV-related hepatocellular carcinoma in Chinese

BackgroundRecently, a genome-wide association study conducted in Chinese reported a single nucleotide polymorphism at KIF1B, rs17401966, associated with the susceptibility of hepatitis B virus-related hepatocellular carcinoma. In this study, we aim to investigate the effect of rs17401966 on the prognosis of hepatitis B virus-related hepatocellular carcinoma patients at intermediate or advanced stages.MethodsThe SNP rs17401966 was genotyped using the TaqMan allelic discrimination assay in 414 intermediate or advanced hepatocellular carcinoma patients. Log-rank test and Cox proportional hazard models were used for survival analyses.ResultsPrevious studies have identified that the G allele of rs17401966 demonstrated protective effect for the susceptibility of hepatitis B virus-related hepatocellular carcinoma. Here we found that subjects carrying the G allele of rs17401966 was significantly associated with a better survival compared with those carrying the A allele (adjusted hazard ratio = 0.82, 95% confidence intervals = 0.68–0.99, P = 0.044 in an additive genetic model).ConclusionThe variant G allele of rs17401966 may be a favorable biomarker for the prognosis of intermediate or advanced hepatitis B virus-related hepatocellular carcinoma patients in this Chinese population.     

Comparison of different deep learning architectures for synthetic CT generation from MR images

PurposeAmong the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigated the performance of some most popular deep learning architectures including eCNN, U-Net, GAN, V-Net, and Res-Net for the task of sCT generation. As a baseline, an atlas-based method is implemented to which the results of the deep learning-based model are compared.MethodsA dataset consisting of 20 co-registered MR-CT pairs of the male pelvis is applied to assess the different sCT production methods' performance. The mean error (ME), mean absolute error (MAE), Pearson correlation coefficient (PCC), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) metrics were computed between the estimated sCT and the ground truth (reference) CT images.ResultsThe visual inspection revealed that the sCTs produced by eCNN, V-Net, and ResNet, unlike the other methods, were less noisy and greatly resemble the ground truth CT image. In the whole pelvis region, the eCNN yielded the lowest MAE (26.03 ± 8.85 HU) and ME (0.82 ± 7.06 HU), and the highest PCC metrics were yielded by the eCNN (0.93 ± 0.05) and ResNet (0.91 ± 0.02) methods. The ResNet model had the highest PSNR of 29.38 ± 1.75 among all models. In terms of the Dice similarity coefficient, the eCNN method revealed superior performance in major tissue identification (air, bone, and soft tissue).ConclusionsAll in all, the eCNN and ResNet deep learning methods revealed acceptable performance with clinically tolerable quantification errors.     

Spatio-temporal modelling of particulate matter concentrations using satellite derived aerosol optical depth over coastal region of Chennai in India

The present study primarily focuses on describing aerosol optical depth (AOD), its distribution pattern and seasonal variation, and modelling Particulate Matter Concentrations in Chennai. The frequency distribution of AOD and PM_2.5 demonstrates that AOD can be used as a proxy for estimating PM_2.5 in the study region as the occurrence of AOD almost resonates with that of PM_2.5. The seasonal variation of AOD and PM_2.5 revealed that during the winter (October–January) and summer (February–May) seasons, AOD reasonably followed the trend of PM_2.5. However, during the monsoon period, AOD showed random variations. Different models like linear and non-linear regression models and machine learning models such as random forest (RF) have been developed for PM_2.5 estimation. The model's performance in different stations and seasons has been assessed. The effect of meteorology and other factors in the model has also been assessed. From linear and non-linear model analysis, AOD was a significant parameter in estimating PM_2.5. The Random Forest model was the stable model for the study region, with a model R² of 0.53 and an RMSE of 15.89 μg/m³. The inclusion of meteorological parameters like relative humidity, wind speed, and wind direction decreased the error in prediction by 17.45 μg/m³. The seasonal and spatial analysis indicates that the prediction capability of models varies with stations and seasons. The best performing model was found to be Model RF, and the model could explain about 53.14% of the variability in PM_2.5 concentration occurrence in the study region with a prediction error of 15.89 μg/m³.     

Dissecting the role of a large chromosomal inversion in life history divergence throughout the Mimulus guttatus species complex

Chromosomal inversions can play an important role in adaptation, but the mechanism of their action in many natural populations remains unclear. An inversion could suppress recombination between locally beneficial alleles, thereby preventing maladaptive reshuffling with less‐fit, migrant alleles. The recombination suppression hypothesis has gained much theoretical support but empirical tests are lacking. Here, we evaluated the evolutionary history and phenotypic effects of a chromosomal inversion which differentiates annual and perennial forms of Mimulus guttatus. We found that perennials likely possess the derived orientation of the inversion. In addition, this perennial orientation occurs in a second perennial species, M. decorus, where it is strongly associated with life history differences between co‐occurring M. decorus and annual M. guttatus. One prediction of the recombination suppression hypothesis is that loci contributing to local adaptation will predate the inversion. To test whether the loci influencing perenniality pre‐date this inversion, we mapped QTLs for life history traits that differ between annual M. guttatus and a more distantly related, collinear perennial species, M. tilingii. Consistent with the recombination suppression hypothesis, we found that this region is associated with life history in the absence of the inversion, and this association can be broken into at least two QTLs. However, the absolute phenotypic effect of the LG8 inversion region on life history is weaker in M. tilingii than in perennials which possess the inversion. Thus, while we find support for the recombination suppression hypothesis, the contribution of this inversion to life history divergence in this group is likely complex.     

Studies on molecular structure and tautomerism of a vitamin B<Subscript>6</Subscript> analog with density functional theory

This work presents a computational study on the molecular structure and tautomeric equilibria of a novel Schiff base L derived from pyridoxal (PL) and o-phenylenediamine by using the density functional method B3LYP with basis sets 6-31 G(d,p), 6-31++G(d,p), 6-311 G(d,p) and 6-311++G(d,p). The optimized geometrical parameters obtained by B3LYP/6-31 G(d,p) method showed the best agreement with the experimental values. Tautomeric stability study of L inferred that the enolimine form is more stable than its ketoenamine form in both gas phase and solution. However, protonation of the pyridoxal nitrogen atom (LH) have accelerated the formation of ketoenamine form, and therefore, both ketoenamine and enolimine forms could be present in acidic media.     

Association between polymorphisms of matrix metalloproteinase 11 (MMP-11) and Kawasaki disease in the Korean population

AimsThis study was conducted to investigate the associations between single nucleotide polymorphisms (SNPs) of matrix metalloproteinases (MMPs) and Kawasaki disease (KD) in the Korean population.Main methodsA total 0f 101 KD patients and 306 healthy controls were examined. MMP7 (rs10502001, G/A, Arg77His), MMP11 (rs738792, T/C, Ala38Val), MMP12 (rs652438, A/G, Ile357Val) and MMP26 (rs2499953, A/G, Lys43Glu) genes were genotyped from the genomic DNA using direct sequencing. The results were then analyzed using logistic regression models, adjusting for gender as covariates.Key findingsThe four SNPs were in Hardy–Weinberg equilibrium. Only the MMP11 polymorphism (rs738792) was associated with KD. The SNP (rs738792) showed a statistically significant association with KD in the codominant (OR = 1.61, 95% CI = 1.11–2.34, P = 0.011) and dominant (OR = 1.92, 95% CI = 1.21–3.06, P = 0.006) models. However, there was no association between polymorphisms of other MMP genes and KD.SignificanceOverall, the results of this study indicate that MMP11 polymorphism may be associated with KD in the Korean population.     

Influence of interleukin 17 A and 17 F polymorphisms in keratoconus

Background

Until a few years ago, keratoconus was defined as a noninflammatory degenerative disease. However, recent studies have shown that the altered balance between inflammatory cytokines, proteases, and protease inhibitors, as well as free radicals and oxidants, have a crucial role in the pathogenesis of this disease. The aim of this study is to investigate whether interleukin 17 A G197A (rs2275913) and interleukin 17 F T7488C (rs763780) polymorphisms are associated with keratoconus in patients from a population of the northwestern region of the State of São Paulo, Brazil.

Methods and Results

35 patients and 61 controls were enrolled. Genotyping of interleukin 17 A G197A and interleukin 17 F T7488C polymorphisms was carried out using the polymerase chain reaction-restriction fragment length polymorphism technique. Statistical analyses were conducted using the chi-square test, and an odds ratio with a 95% confidence interval was also calculated to evaluate the association between polymorphisms and disease. Evaluating interleukin 17 F T7488C, we found that the TT genotype is associated as a risk factor for keratoconus (P?=?0.04; OR?=?3.01; CI 1.11–8.14). As for evaluating interleukin 17 A G197A, the allele and genotype frequencies between patients and controls were compared and no statistically significant differences were found.

Conclusions

Our data showed that the interleukin 17 F T7488C polymorphisms may exert an influence in keratoconus.

     

Validation of Bayesian analysis of compartmental kinetic models in medical imaging

IntroductionKinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated.Materials and methodsThe closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach.Results and discussionPosteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P > 0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P < 0.0001).ConclusionsThe results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities.     

Testing Taxon Tenacity of Tortoises: evidence for a geographical selection gradient at a secondary contact zone

We examined a secondary contact zone between two species of desert tortoise, Gopherus agassizii and G. morafkai. The taxa were isolated from a common ancestor during the formation of the Colorado River (4–8 mya) and are a classic example of allopatric speciation. However, an anomalous population of G. agassizii comes into secondary contact with G. morafkai east of the Colorado River in the Black Mountains of Arizona and provides an opportunity to examine reinforcement of species' boundaries under natural conditions. We sampled 234 tortoises representing G. agassizii in California (n = 103), G. morafkai in Arizona (n = 78), and 53 individuals of undetermined assignment in the contact zone including and surrounding the Black Mountains. We genotyped individuals for 25 STR loci and determined maternal lineage using mtDNA sequence data. We performed multilocus genetic clustering analyses and used multiple statistical methods to detect levels of hybridization. We tested hypotheses about habitat use between G. agassizii and G. morafkai in the region where they co‐occur using habitat suitability models. Gopherus agassizii and G. morafkai maintain independent taxonomic identities likely due to ecological niche partitioning, and the maintenance of the hybrid zone is best described by a geographical selection gradient model.     

Association between TNF-α-308 G/A gene polymorphism and gastric cancer risk: A systematic review and meta-analysis

ObjectiveTumor necrosis factor-alpha (TNF-α) has been found to be associated with gastric carcinogenesis, but individually published results have been inconclusive. The aim of this study was to explore the relationship between the TNF-α-308 G/A polymorphism and gastric cancer risk.MethodsMEDLINE, EMBASE and the COCHRANE library databases were searched for relevant articles to identify all available data. The odds ratios (ORs) with 95% confidence intervals (95% CIs) from each study were used to assess the association between the TNF-α-308 G/A polymorphism and gastric cancer risk.ResultsThis meta-analysis included 30 studies (32 datasets) involving 7009 gastric cancer cases and 12,119 control subjects. Overall, a significant association was found between the TNF-α-308 G/A polymorphism and gastric cancer in AA + GA vs. GG (dominant contrast model) (OR = 1.20, 95% CI = 1.07–1.34, p = 0.001). With stratification based on ethnicity, the TNF-α-308 G/A polymorphism was correlated with gastric cancer risk in Caucasians, using the dominant contrast model (OR = 0.74, 95% CI = 0.57–0.96, p = 0.02), but not in East Asians and other ethnic groups. In the comprehensive subgroup analysis, a significant association was also found in recent articles (published after 2005), population-based high-quality studies, hospital-based high-quality studies, studies using the TaqMan method and non-cardia subgroups. However, the TNF-α-308 G/A polymorphism was not associated with specific histological types of gastric cancer risk.ConclusionsThe TNF-α-308 G/A polymorphism may contribute to susceptibility to gastric cancer in Caucasians, especially for non-cardia gastric cancer, as most strongly demonstrated in high-quality studies and in studies using the TaqMan genotyping method. Furthermore, we recommend the TaqMan method as the preferred genotyping method in DNA polymorphism studies.     

Complication probability model for subcutaneous fibrosis based on published data of partial and whole breast irradiation

PurposeTo extend the application of current radiation therapy (RT) based normal tissue complication probability (NTCP) models of radiation-induced fibrosis (RIF) of the breast to include the effects of fractionation, inhomogeneous dose, incomplete recovery, and time after the end of radiotherapy in partial breast irradiation (PBI).Materials and methodsAn NTCP Lyman model with biologically effective uniform dose (BEUD) with and without a correction for the effect of incomplete repair was used. The time to occurrence of RIF was also taken into account. The radiobiological parameters were determined by fitting incidences of moderate/severe RIF in published randomized studies on RT of the breast. The NTCP model was used to calculate the risk of toxicity in 35 patients treated with intensity modulated, non-accelerated PBI and the result was compared with observed incidence of RIF.ResultsWith α/β fixed at 3Gy the parameters of the model without correction for incomplete repair extracted from fitting were: 50% complication probability biologically effective dose BEUD₅₀ = 107.2 Gy (95%CI = 95.9–118.6 Gy), volume parameter n = 0.06 (95%CI = 0–0.23), and slope of dose response m = 0.22, (95%CI = 0.20–0.23). After including the correction for incomplete repair with repair halftime for subcutaneous tissue of τ = 4.4 h we obtained BEUD₅₀ = 105.8 Gy (95%CI = 96.9–114.6Gy), n = 0.15 (95%CI = 0–0.33), m = 0.22 (95%CI = 0.20–0.23). Average NTCP predicted by these models, 4.3% and 2.0% respectively, offered a good agreement with RIF incidence in our patients, 5.7%, after an average follow-up of 12 months.ConclusionThe NTCP models of RIF, incorporating the effects of fractionation, volume effect, and latency of toxicity look promising to model PBI. Clinical validation from a prospective PBI treatment study is under development and will help test this preliminary result.     

Signal-to-noise ratio improvements using anti-scatter grids with different object thicknesses and tube voltages

PurposeThe appropriate object thickness to start using anti-scatter grids (grids) has not sufficiently investigated in previous studies, and thus we rigorously investigated the effectiveness of two generally used grids with grid ratios of 6 and 10 (G6 and G10) for different 50–200 mm thicknesses at tube voltages of 60–100 kV.MethodsAcrylic phantoms with 30 × 30 cm² and different thicknesses were used to measure the signal-to-noise ratio improvement factors (SIFs) of grids. To evaluate the infants’ conditions, field sizes of 225, 400, and 625 cm² were also evaluated at 60–80 kV. In addition, the signal difference-to-noise ratio (SDNR) was used to evaluate tube voltage dependencies of grids for each thickness.ResultsSIF values exceeded 1.0 for ≥70 mm thicknesses and mostly exceeded 1.07 for the 100 mm thickness with 400 cm² field size corresponding to a 1-year-old infant abdomen. The estimated dose reduction capabilities for a 1-year-old infant were approximately 15% using G10 at 70 and 80 kV. The tube voltage dependencies for grid use was almost not prominent for all conditions tested, except for some conditions that are not clinically realistic.ConclusionsG6 and G10 can improve SNR for  ≥100 mm thickness. The results from this work demonstrate approximately 15% dose reduction or image quality improvements at the same dose level for the use of G6 and G10 grids for 100 mm thickness, traditionally excluded from the recommended grid use conditions.     

Targeting the G-quadruplex-forming region near the P1 promoter in the human BCL-2 gene with the cationic porphyrin TMPyP4 and with the complementary C-rich strand

The B-cell lymphoma-2 (bcl-2) gene contains a region that has been implicated in the regulation of bcl-2 gene expression. This region can form G-quadruplex structures in solution [J.X. Dai, T.S. Dexheimer, D. Chen, M. Carver, A. Ambrus, R.A. Jones, D.Z. Yang, An intramolecular G-quadruplex structure with mixed parallel/antiparallel G-strands formed in the human BCL-2 promoter region in solution, J. Am. Chem. Soc. 128 (2006) 1096–1098.]. Here, we examined the acid–base and conformational equilibria of this G-quadruplex-forming region (BCL2G), as well as its interaction with both the porphyrin TMPyP4 and with the complementary C-rich strand. We used molecular absorption and circular dichroism techniques, in tandem with multivariate analysis tools. The results revealed the formation of an interaction complex BCL2G:TMPyP4 with a stoichiometry of 1:2 and an equilibrium constant equal to 5.0 (±2.3) × 10¹³ M⁻². Addition of the complementary C-rich strand to BCL2G induces the predominant formation of the Watson–Crick double-helix with an equilibrium constant equal to 10^7.7 M⁻¹ (at pH 7.1). Finally, the pH-induced formation of quadruplex structures from the Watson–Crick double-helix is characterized.     

Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy

PurposeImage-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions.MethodsUsing a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D₉₈, D₅₀ and D₂ of the target volume) and 3D-gamma (3%/3mm) analysis were performed.ResultsThe mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases.ConclusionsThe presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled.     

Temperature-dependent development of diapausing larvae of Chilo partellus (Swinhoe) (Lepidoptera: Crambidae)

Temperature-dependent development rate, percent diapause induction (hibernation at low temperature and aestivation at high temperature), and survival of diapausing larvae of Chilo partellus (Swinhoe, 1885) were examined on 13 constant temperatures ranging from 8 to 40 °C. Development of hibernating and aestivating larvae occurred from 10 to 25 °C and 27–38 °C, respectively. However, no development occurred at 8 °C and 40 °C. To determine actual thermal conditions that affect development and trigger both kind of diapause (hibernation and aestivation), various thermal parameters were estimated by fitting the development rate data to two linear (Ordinary equation and Ikemoto & Takai) models and thirteen non-linear models. The lower thermal thresholds (T_min) for development of diapausing larvae of C. partellus were calculated as 9.60 °C and 10.29 °C using the ordinary linear model and Ikemoto & Takai model, respectively. Similarly, the thermal constants (K) estimated using the ordinary linear model was 333.33 degree-days and that estimated with Ikemoto & Takai model was 338.92 degree-days. Among the non-linear models, Lactin-2 followed by Lactin-1 were found to be the best as these models estimated the critical temperatures (T_min, T_max and T_opt) similar to those of observed values. Conclusively, the Ikemoto & Takai linear model and Lactin-2 followed by Lactin-1 non-linear models are useful and efficient for describing temperature-dependent development and estimating the temperature thresholds of diapausing larvae of C. partellus. Our findings provided fundamental information for estimation of thermal requirement and temperature based development models for diapausing larvae of C. partellus. This information will be highly useful for predicting the occurrence, seasonal emergence, number of generations and population dynamics of C. partellus.