Outcome in patients of hormone receptor (HR) positive (Her 2) negative metastatic breast cancer treated with palbociclib – A real-world experience

Objectives: We present real-world outcome with the use of palbociclib in patients with HR-positive Her2-negative breast cancer treated at single center in India. Material and Methods: We conducted a medical audit of consecutive patients with HR-positive Her2-negative metastatic breast cancer, who were treated with palbociclib at our center between November 2016 and May 2020. Palbociclib was commenced at a dose of 125 mg orally once daily and a schedule of 21 days on therapy followed by 7 days off therapy was followed. Survival analysis included the Kaplan–Meier method using Statistical Package for the Social Sciences software (Version 26). HRs were calculated using Cox proportional hazard regression models and 95% confidence intervals (CIs) for the incidence estimates. Results: A total of 67 female patients were commenced on treatment with palbociclib between November 2016 and May 2020. The median age was 55 years (range 29–78 years). A total of 51 (76%) of these patients were postmenopausal and the remaining 16 were premenopausal. Baseline metastatic disease involved one organ/site in 23 (34%), two organs/sites in 32 (48%), three or more in 12 (18%). Bony metastasis alone was seen in 17 (25%) patients, visceral alone in 30 (45%), and the remaining 20 had both bony and visceral metastases. For these 67 patients, palbociclib was commenced as 1st line systemic therapy in 24 (36%) cases. Amongst the remaining 43 cases, it was 2nd line in 21 (31%); 3rd line and beyond in 22 (33%). Median PFS was 16.1 months (95% CI: 9.6–22.8) and median OS was 20.7 months (95% CI: 14.1–27.3). Median PFS for palbociclib use in first line was 18.7 months (95% CI: 4.6–32.9) while in subsequent lines, it was 13.8 months (95% CI: 9.8–17.9; log-rank P = 0.228). Median OS in patients who received palbociclib in first line was 23.2 months (95 % CI 20.1–26.3) and for those why received it in subsequent lines was 16.3 months (95 % CI: 12.5–20.1; P = 0.069). In total population, best response on imaging was CR in 11 (16%) cases (06 in 1st line setting and 05 in subsequent line setting); PR in 33 (49%); SD in 03; and progressive disease in 20. Median PFS with bone only metastasis: 20.9 months (95 % CI: 5.9–36.0), while with visceral metastasis 16.1 months (95% CI: 9.8–22.5; P = 0.537). Median OS with bone only metastasis: 22.7 months (95% CI: 17.8–27.5), while with visceral metastasis, it was 18.5 months (95% CI: 13.6–23.4; P = 0.314). Conclusion: Palbociclib is a useful addition in the management of HR +ve Her2 –ve breast cancer patients. Its benefit is confirmed in our real-world setting, both in the first and subsequent lines of therapy and the data are on similar lines as the global real-world data on palbociclib effectiveness.

The pan-immune-inflammation value and systemic immune-inflammation index in advanced melanoma patients under immunotherapy

Purpose To evaluate the pan-immune-inflammation value (PIV) and systemic immune-inflammation index (SII) in patients with cutaneous melanoma (CM) under immune checkpoint inhibitor (ICI) therapy. Methods PIV and SII were calculated before the start of ICI therapy and at time of progression/death in patients with metastatic CM (stage III/IV). Sex–age-matched CM patients in stage I/II and healthy subjects (HC) served as controls. Results The median PIV of stage III/IV patients was significantly (P = 0.0011) higher than in stage I/II patients and HC. SII was significantly (P = 0.00044) lower in HC than in CM patients. At baseline, PIV and SII did significantly correlate with lactate dehydrogenase (P = 0.045/0.017). However, ROC curve statistics revealed that SII and PIV were not significantly associated with clinical parameters, including best response to ICI treatment (P = 0.87/0.64), progression-free survival (P = 0.73/0.91), and melanoma-specific survival (P = 0.13/0.17). Moreover, there were no significant changes of PIV and SII from baseline to progression/death (P = 0.38/0.52). Conclusions Even though both immune-inflammation biomarkers showed some power to differentiate between CM stages and HC, respectively, PIV and SII seem not to be significant predictors for clinical outcome measures of CM patients under ICI therapy.

Changes in Serum Growth Factors during Lenvatinib Predict the Post Progressive Survival in Patients with Unresectable Hepatocellular Carcinoma

Serum growth factor changes and their effect on prognosis during lenvatinib for unresectable hepatocellular carcinoma (HCC) remain underexplored. The sequential changes in serum growth factors during lenvatinib for unresectable HCC were evaluated in 58 patients using complete clinical data, and preserved serum was used to investigate changes in FGF-19, ANG-2, HGF, VEGF, and EGF. Patients with a complete response (CR), partial response (PR), and stable disease (SD) were evaluated for growth factor changes between the best response and progressive disease (PD) points, classified based on these changes, and evaluated by post progression survival (PPS). A total of 8, 24, 18, and 8 patients showed CR, PR, SD, and PD, respectively. Multivariate analysis revealed that age, relative dose intensity, and baseline ANG-2 were significantly associated with treatment response. Growth factor changes between the best response and PD points revealed that patients could be classified into four groups based on the EGF, ANG-2, and HGF changes. Although patient characteristics at baseline and PD, their response to lenvatinib, and PFS were similar among those groups, patients with an increase in all growth factors had significantly shorter PPS (median PPS was 553, 323, and 316 versus 173 days in groups 1–4 p = 0.032). We revealed that the evaluation of the changes in growth factors during lenvatinib could predict PPS.

Residential Short-Term Load Forecasting during Atypical Consumption Behavior

Short-term load forecasting (STLF) is a fundamental tool for power networks’ proper functionality. As large consumers need to provide their own STLF, the residential consumers are the ones that need to be monitored and forecasted by the power network. There is a huge bibliography on all types of residential load forecast in which researchers have struggled to reach smaller forecasting errors. Regarding atypical consumption, we could see few titles before the coronavirus pandemic (COVID-19) restrictions, and afterwards all titles referred to the case of COVID-19. The purpose of this study was to identify, among the most used STLF methods—linear regression (LR), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN)—the one that had the best response in atypical consumption behavior and to state the best action to be taken during atypical consumption behavior on the residential side. The original contribution of this paper regards the forecasting of loads that do not have reference historic data. As the most recent available scenario, we evaluated our forecast with respect to the database of consumption behavior altered by different COVID-19 pandemic restrictions and the cause and effect of the factors influencing residential consumption, both in urban and rural areas. To estimate and validate the results of the forecasts, multiyear hourly residential consumption databases were used. The main findings were related to the huge forecasting errors that were generated, three times higher, if the forecasting algorithm was not set up for atypical consumption. Among the forecasting algorithms deployed, the best results were generated by ANN, followed by ARIMA and LR. We concluded that the forecasting methods deployed retained their hierarchy and accuracy in forecasting error during atypical consumer behavior, similar to forecasting in normal conditions, if a trigger/alarm mechanism was in place and there was sufficient time to adapt/deploy the forecasting algorithm. All results are meant to be used as best practices during power load uncertainty and atypical consumption behavior.

Interruption of Seed Dormancy and In Vitro Germination of the Halophile Emerging Crop Suaeda edulis (Chenopodiaceae)

Suaeda edulis (Flores Olvera & Noguez) is a halophile species that grows in saline environments, with concomitant difficulties to germinate and reproduce. Once a null germination under a salinity gradient or fresh water was observed, a plant-growth bioregulator (BioR) was applied to interrupt dormancy and improve germination in vitro. This BioR is composed of gibberellins and adjuvant regulators; and 12.5, 25.0, and 37.5 mg L−1 of gibberellins with immersion at 24, 48, and 72 h were assayed. Most of the normality and homoscedasticity tests were favorable, except in three of 24 cases. On the germination percentage (transformed values), the dose 25.0 mg L−1 reflected the highest values of 5.5 and 6.0 units at 48 and 72 h. For the mean germination time, the highest level of 37.5 mg L−1 at 24 h reflected the best response. For the germination rate, the best one was 25 mg L−1 at 48 h, reaching 12% per day, but for the germination speed coefficient, the best value was observed with 25.0 mg L−1 at 24 h. It was concluded that to improve germination of S. edulis seeds, it is necessary to assess a dose-gradient of gibberellins, starting at 25.0 mg L−1, with higher values to break dormancy.

Aklimatisasi dan Respon Pertumbuhan Mutan Leucaena Leucocephala Varietas Tarramba Teradaptasi Asam

Acclimatization is the final stage of plant propagation in tissue culture techniques that can determine the success of the nursery process. This study aimed to observe the growth response during the acclimatization stage of the acid-adapted of Leucaena leucocephala Tarramba variety, which developed from tissue culture techniques. The design used in this study was a completely randomized design (CRD) with the cultivation of 11 mutant lines from tissue culture, namely M1-M11 (an acid-adapted mutant from tissue culture addition of 1 ppm IBA) and 2 controls (lamtoro broodstock without gamma irradiation) namely K0 (lamtoro broodstock resulting from tissue culture addition of 0 ppm IBA), K1 (breeding lamtoro from tissue culture addition of 1 ppm IBA). The variables observed were the level of plant viability, plant height, and number of leaves. The results showed that the acclimatization of the plant Leucaena leucocephala to tissue culture production on the M3 and M9 mutant lines gave the best response to plant morphological growth up to 5 WAP (weeks after planting). Key words: acclimatization, IBA hormone, Leucaena leucocephala, tissue culture

A Result on Convergence of Sequences of Iterations with Applications to Best-Response Dynamics

The result that says the sequence of iterations [Formula: see text] converges if [Formula: see text] is an increasing function has numerous applications in elementary economic analysis. I generalize this simple result to some mappings [Formula: see text]. The applications of the new result include the convergence of the best-response dynamics in the general version of the Crawford and Sobel model and in some versions of the Hotelling and Tiebout models.

Development of An Efficient Protocol for Rapid Propagation of Curculigo orchioides Using Leaf Explant Culture

Curculigo orchioides is one of the most common medicinal plants used by diverse cultures and tribal groups. The roots of the plant are used medicinally in Asian countries. Curculigo orchioides have the ability to regenerate through seeds and tubers, but the regeneration rate is low. Plant tissue culture method was believed to have potential for rapid multiplication of this medicinal plant. An efficient protocol for rapid propagation of Curculigo orchioides, of the family Amaryllidaceae, was developed using leaf explants culture. The leaf explants (1 cm x 1 cm squares) cultured on Murashige and Skoog (MS) basal medium were supplemented with various concentrations and combinations of auxins and cytokinins with temperature 25 ± 2°C, relative humidity 85-90% and photoperiod of 12 hours light (2000-3000 lux). Callus induction was obtained within 4 weeks, 2,4-D at 3 mg/l formed profuse callus and the degree was found to be the highest (+++) among all the treatments. The best response to shoot induction, with maximum shoot number 5.33 (mean number of shoots per explant) was obtained using 1.0 mg/l 6-benzyl aminopurine (BAP) in combination with 1.0 mg/l Kinetin. In vitro shoots were induced for rooting on 0.5 mg/l of NAA supplemented medium. In order for seedlings propagated in vitro to adapt to natural conditions, plants were growned on a substrate coir: husk ash: sand (with the ratio of 0.5: 0.5: 1) in a greenhouse (humidity: 70%, temperature: 28-300C) gave 88.33% survival rate after 8 weeks of culture. With the results received, this is an effective approach to propagating Curculigo orchioides.

Salp Swarm Optimization Algorithm for Estimating the Parameters of Photovoltaic Panels Based on the Three-Diode Model

Due to the the lack of information about parameters in the datasheets of photovoltaic (PV) panels, it is difficult to study their modeling because PV behavior is based on voltage–current (V-I) data, which present a highly nonlinear relationship. To solve this difficulty, this study presents a mathematical three-diode model of a PV panel that includes multiple unknown parameters: photoinduced current, saturation currents of the three diodes, three ideality factors, serial resistance, and parallel resistance. These parameters should be estimated in the three-diode model of a PV panel to obtain the actual values that represent the voltage–current profile or the voltage–power profile (because of its visual simplicity) of the PV panel under analysis. In order to solve this problem, this paper proposes a new application of the salp swarm algorithm (SSA) to estimate the parameters of a three-diode model of a PV panel. Two test scenarios were implemented with two different PV panels, i.e., Kyocera KC200GT and Solarex MSX60, which generate different power levels and are widely used for commercial purposes. The results of the simulations were obtained using different irradiance levels. The proposed PV model was evaluated based on the experimental results of the PV modules analyzed in this paper. The efficiency of the optimization technique proposed here, i.e., SSA, was measured by a fair comparison between its numerical results and those of other optimization techniques tuned to obtain the best response in terms of the objective function.