A unified framework of response surface methodology and coalescing of Firefly with random forest algorithm for enhancing nano-phytoremediation efficiency of chromium via in vitro regenerated aquatic macrophyte coontail (Ceratophyllum demersum L.).

Nano-phytoremediation is a novel green technique to remove toxic pollutants from the environment. In vitro regenerated Ceratophyllum demersum (L.) plants were exposed to different concentrations of chromium (Cr) and exposure times in the presence of titania nanoparticles (TiO2NPs). Response surface methodology was used for multiple statistical analyses like regression analysis and optimizing plots. The supplementation of NPs significantly impacted Cr in water and Cr removal (%), whereas NP × exposure time (T) statistically regulated all output parameters. The Firefly metaheuristic algorithm and the random forest (Firefly-RF) machine learning algorithms were coalesced to optimize hyperparameters, aiming to achieve the highest level of accuracy in predicted models. The R2 scores were recorded as 0.956 for Cr in water, 0.987 for Cr in the plant, 0.992 for bioconcentration factor (BCF), and 0.957 for Cr removal through the Firefly-RF model. The findings illustrated superior prediction performance from the random forest models when compared to the response surface methodology. The conclusion is drawn that metal-based nanoparticles (NPs) can effectively be utilized for nano-phytoremediation of heavy metals. This study has uncovered a promising outlook for the utilization of nanoparticles in nano-phytoremediation. This study is expected to pave the way for future research on the topic, facilitating further exploration of various nanoparticles and a thorough evaluation of their potential in aquatic ecosystems.

Artificial intelligence models for validating and predicting the impact of chemical priming of hydrogen peroxide (H2O2) and light emitting diodes on in vitro grown industrial hemp (Cannabis sativa L.).

Industrial hemp (Cannabis sativa L.) is a highly recalcitrant plant under in vitro conditions that can be overcome by employing external stimuli. Hemp seeds were primed with 2.0-3.0% hydrogen peroxide (H2O2) followed by culture under different Light Emitting Diodes (LEDs) sources. Priming seeds with 2.0% yielded relatively high germination rate, growth, and other biochemical and enzymatic activities. The LED lights exerted a variable impact on Cannabis germination and enzymatic activities. Similarly, variable responses were observed for H2O2 × Blue-LEDs combination. The results were also analyzed by multiple regression analysis, followed by an investigation of the impact of both factors by Pareto chart and normal plots. The results were optimized by contour and surface plots for all parameters. Response surface optimizer optimized 2.0% H2O2 × 918 LUX LEDs for maximum scores of all output parameters. The results were predicted by employing Multilayer Perceptron (MLP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Moreover, the validity of these models was assessed by using six different performance metrics. MLP performed better than RF and XGBoost models, considering all six-performance metrics. Despite the differences in scores, the performance indicators for all examined models were quite close to each other. It can easily be concluded that all three models are capable of predicting and validating data for cannabis seeds primed with H2O2 and grown under different LED lights.

Prevalence of gestational diabetes mellitus in Pakistan: a systematic review and meta-analysis.

BACKGROUND: A variety of screening tools and criteria are used for the diagnosis of gestational diabetes mellitus (GDM). As a result, the prevalence rate of GDM varied from 4.41% to 57.90% among studies from Pakistan. Beside this disagreement, similar multi-centric studies, community surveys and pooled evidence were lacking from the country. Therefore, this first systematic review and meta-analysis aimed to measure the overall and subgroup pooled estimates of GDM and explore the methodological variations among studies for any inconsistency. METHODS: Using the PRISMA guidelines, seventy studies were identified from PubMed, ScienceDirect, Google Scholar and PakMediNet database. Of them, twenty-four relevant studies were considered for systematic review and nine eligible studies selected for meta-analysis. AXIS was used for measuring quality of reporting, I^2 statistics for heterogeneity among studies and subgroups, funnel plot for reporting potential publication bias and forest plot for presenting pooled estimates. RESULTS: The pooled sample of nine studies was 27,034 (126 - 12,450) pregnant women, of any gestational age, from all four provinces of Pakistan. Overall pooled estimate of GDM was 16.7% (95% CI 13.1 - 21.1). The highest subgroup pooled estimate of GDM observed in studies from Balochistan (35.8%), followed by Islamabad (23.9%), Khyber Pakhtunkhwa (17.2%), Sindh (13.2%), and Punjab (11.4%). The studies that adopted 75g 2-h OGTT had a little lower pooled estimate (16.3% vs. 17.3%); and that adopted diagnostic cut-off values [≥ 92 (F), ≥ 180 (1-h) and ≥ 153 (2-h)] had a greater pooled estimate (25.4% vs. 15.8%). The studies that adopted Carpenter criteria demonstrated the highest subgroup pooled estimate of GDM (26.3%), after that IADPSG criteria (25.4%), and ADA criteria (23.9%). CONCLUSIONS: Along with poor quality of reporting, publishing in non-indexed journals and significant disagreement between studies, the prevalence rate of GDM is high in Pakistan. Consensus building among stakeholders for recommended screening methods; and continuous medical education of the physicians are much needed for a timely detection and treatment of GDM.

Height-for-age and weight-for-age growth charts for Pakistani infants under six months: derived from a novel case selection method using multiple indicator cluster survey data.

BACKGROUND: In the past two decades, there has been a growing recognition of the need to establish indigenous standards or reference growth charts, particularly following the WHO multicenter growth study in 2006. The availability of accurate and reliable growth charts is crucial for monitoring child health. The choice of an appropriate model for constructing growth charts depends on various data characteristics, including the distribution's tails and peak. While Pakistan has reported some reference growth charts, there is a notable absence of indigenous charts for children under two years of age, especially for infants aged 0-6 months who are exclusively breastfed. Additionally, acquiring data poses a significant challenge, particularly for low-income countries, as it demands substantial resources such as finances, time, and expertise. The Multiple Indicator Cluster Survey (MICS) constitutes a large-scale national survey conducted periodically in low-income countries under the auspices of UNICEF. In this study, we propose methods for generating selection variables utilizing the "Novel Case Selection Method," as previously published. Further our approach enables to select and fit appropriate model to the MICS data, selected, and to develop the standard growth charts. METHODS: Out of the 11,478 children under 6 months of age included in MICS-6 (Pakistan), 3,655 children (1,831 males and 1,824 females) met the specified criteria and were selected using the "Novel Case Selection Method". The sample was distributed across provinces as follows: 841 (23.0%) from KPK, 1,464 (40.1%) from Punjab, 819 (22.4%) from Sindh, and 531 (14.5%) from Balochistan. This sample encompassed both rural (76.4%) and urban (23.6%) populations. Following data cleaning and outlier removal, a total of 3,540 records for weight (1,768 males and 1,772 females) and 3,515 records for height (1,759 males and 1,756 females) were ultimately available for the development of standard charts. The Bayesian Information Criterion (BIC) was employed to determine the optimal degrees of freedom for L, M, and S using RefCurv_0.4.2. Three families within the gamlss class-namely, Box Cox Cole and Green (BCCG), Box Cox T (BCT), and Box Cox Power Exponential (BCPE)-were applied, each with three smoothing techniques: penalized splines (ps), cubic splines (cs), and polynomial splines (poly). The best-fitted model was selected from these nine combinations based on the Akaike Information Criteria. RESULTS: The Novel Case Selection Method yielded 3655 cases as per criteria. After cleaning the data, this method lead to selection of 3540 children for "weight for age" (W/A) and 3515 children for "height for age" (H/A). The "BCPE" family and "ps" as smoothing method proved to be best on AIC for all four curves, i.e. the W/A male, W/A female, H/A male, and H/A female. The optimum selected degrees of freedom for the curve "W/A", for both genders were (M = 1, L = 0, S = 0). The optimum degrees of freedom for H/A male were again (M = 1, L = 0, S = 0), but for females the selected degrees of freedom were (M = 1, L = 1, S = 1). The indigenous fitted standard curves for Pakistan were on lower trajectory in comparison to WHO standards. CONCLUSION: This study uses the Novel Case Selection Method with introduced algorithms to construct tailored growth charts for lower and middle-income countries. Leveraging extensive MICS data, the methodology ensures representative national samples. The resulting charts hold practical value and await validation from established data sources, offering valuable tools for policy makers and clinicians in diverse global contexts.

Heterologous expression of bacterial dehydrin gene in Arabidopsis thaliana promotes abiotic stress tolerance.

Salinity, low temperature, and drought are major environmental factors in agriculture leading to reduced crop yield. Dehydrins (DHNs) are induced transcriptionally during cellular dehydration and accumulate in different tissues during abiotic stresses. Here we isolated and characterized a bacterial gene BG757 in Arabidopsis, encoding a putative dehydrin type protein. ABA induces the expression of various dehydrins in plants, therefore, to elucidate the potential role, ABA sensitivity was examined in Arabidopsis transgenic lines expressing BG757. Interestingly, BG757-expressing plants showed hypersensitivity towards NaCl and ABA during seed germination. In addition to germination, BG757-expressing plants also showed root growth retardation in the presence of ABA and NaCl when compared with wild type (WT), suggesting that BG757 positively regulate salt stress and ABA response. Furthermore, BG757-expressing plants showed significant drought tolerance compared with WT. Consistent with drought tolerance, expression levels of stress inducible genes (DREB2A, RD22, RD26, LEA7 and SOS1) were strongly upregulated in transgenic plants compared with WT. All together these results suggest that heterologous expression of bacterial gene, BG757 in plants promotes resistance to environmental stresses. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01358-w.

Solvent based fractional biosynthesis, phytochemical analysis, and biological activity of silver nanoparticles obtained from the extract of Salvia moorcroftiana.

Multi-drug resistant bacteria sometimes known as "superbugs" developed through overuse and misuse of antibiotics are determined to be sensitive to small concentrations of silver nanoparticles. Various methods and sources are under investigation for the safe and efficient synthesis of silver nanoparticles having effective antibacterial activity even at low concentrations. We used a medicinal plant named Salvia moorcroftiana to extract phytochemicals with antibacterial, antioxidant, and reducing properties. Three types of solvents; from polar to nonpolar, i.e., water, dimethyl sulfoxide (DMSO), and hexane, were used to extract the plant as a whole and as well as in fractions. The biosynthesized silver nanoparticles in all extracts (except hexane-based extract) were spherical, smaller than 20 nm, polydispersed (PDI ranging between 0.2 and 0.5), and stable with repulsive force of action (average zeta value = -18.55±1.17). The tested bacterial strains i.e., Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus faecalis were found to be sensitive to even small concentrations of Ag-NPs, especially P. aeruginosa. The antibacterial effect of these Ag-NPs was associated with their ability to generate reactive oxygen species. DMSO (in fraction) could efficiently extract antibacterial phytochemicals and showed activity against MDR bacteria (inhibition zone = 11-12 mm). Thus, the antibacterial activity of fractionated DMSO extract was comparable to that of Ag-NPs because it contained phytochemicals having solid antibacterial potential. Furthermore, Ag-NPs synthesized from this extract owned superior antibacterial activity. However, whole aqueous extract-based Ag-NPs MIC was least (7-32 µg/mL) as compared to others.

First-Principles Investigation of Novel Alkali-Based Lead-Free Halide Perovskites for Advanced Optoelectronic Applications.

Lead-free halide perovskites are considered promising candidates as visible light absorbers with outstanding optoelectronic properties. In this work, novel kinds of lead-free halide perovskites were studied for their electronic, optical, and thermoelectric properties by employing the most precise and enhanced modified Trans-Blaha Beck-Johnson potential. The estimated band spectra of the studied materials were comparable. The materials are confirmed to have an indirect band gap semiconducting nature due to the existence of energy band gaps. Among the studied materials, CsSnI3 has a smaller band gap, confirming the excitation to be more energy efficient. Examining the predicted density of states and true electronic orbital contributions, we observed a progressive fluctuation along the energy axis was observed. Furthermore, the linear optical properties are calculated and studied in terms of possible optoelectronic applications. The absorption in KSnI3 was greater compared to the other two materials. The studied materials could be used for antireflecting coatings against UV radiation, owing to the prominent peaks in their reflectivity spectra. The Seebeck coefficient and electrical properties, as well as the positive value of RH all pointed to a p-type nature in these materials. From the anticipated thermoelectric properties, the materials also appear to be suitable for application in thermoelectric devices.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding.

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

Delpinium uncinatum mediated green synthesis of AgNPs and its antioxidant, enzyme inhibitory, cytotoxic and antimicrobial potentials.

Green synthesis of nanoparticles is becoming a method of choice for biological research due to its environmentally benign outcomes, stability and ease of synthesis. In this study, silver nanoparticles (AgNPs) were synthesized using stem (S-AgNPs), root (R-AgNPs) and mixture of stem and root (RS-AgNPs) of Delphinium uncinatum. The synthesized nanoparticles were characterized by standardized techniques and evaluated for their antioxidant, enzyme inhibition, cytotoxic and antimicrobial potentials. The AgNPs exhibited efficient antioxidant activities and considerable enzyme inhibition potential against alpha amylase, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. S-AgNPs showed strong cytotoxicity against human hepato-cellular carcinoma cells (HepG2) and high enzyme inhibitory effect (IC50 values 27.5µg/ml for AChE and 22.60 µg/ml for BChE) compared to R-AgNPs and RS-AgNPs. RS-AgNPs showed significant inhibition of Klebsiella pneumoniae and Aspergillus flavus and exhibited higher biocompatibility (<2% hemolysis) in human red blood cells hemolytic assays. The present study showed that biologically synthesized AgNPs using the extract of various parts of D. uncinatum have strong antioxidant and cytotoxic potentials.

Artificial neural network modeling for deciphering the in vitro induced salt stress tolerance in chickpea (Cicer arietinum L).

Salt stress is one of the most critical abiotic stresses having significant contribution in global agriculture production. Chickpea is sensitive to salt stress at various growth stages and a better knowledge of salt tolerance in chickpea would enable breeding of salt tolerant varieties. During present investigation, in vitro screening of desi chickpea by continuous exposure of seeds to NaCl-containing medium was performed. NaCl was applied in the MS medium at the rate of 6.25, 12.50, 25, 50, 75, 100, and 125 mM. Different germination indices and growth indices of roots and shoots were recorded. Mean germination (%) of roots and shoots ranged from 52.08 to 100%, and 41.67-100%, respectively. The mean germination time (MGT) of roots and shoots ranged from 2.40 to 4.78 d and 3.23-7.05 d. The coefficient of variation of the germination time (CVt) was recorded as 20.91-53.43% for roots, and 14.53-44.17% for shoots. The mean germination rate (MR) of roots was better than shoots. The uncertainty (U) values were tabulated as 0.43-1.59 (roots) and 0.92-2.33 (shoots). The synchronization index (Z) reflected the negative impact of elevated salinity levels on both root and shoot emergence. Application of NaCl exerted a negative impact on all growth indices compared to control and decreased gradually with elevated NaCl concentration. Results on salt tolerance index (STI) also revealed the reduced STI with elevated NaCl concentration and STI of roots was less than shoot. Elemental analysis revealed more Na and Cl accumulation with respective elevated NaCl concentrations. The In vitro growth parameters and STI values validated and predicted by multilayer perceptron (MLP) model revealed the relatively high R 2 values of all growth indices and STI. Findings of this study will be helpful to broaden the understanding about the salinity tolerance level of desi chickpea seeds under in vitro conditions using various germination indices and seedling growth indices. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01282-z.

Artificial intelligence-based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.

Water bodies or aquatic ecosystem are susceptible to heavy metal accumulation and can adversely affect the environment and human health especially in underdeveloped nations. Phytoremediation techniques of water bodies using aquatic plants or macrophytes are well established and are recognized as eco-friendly world over. Phytoremediation of heavy metals and other pollutants in aquatic environments can be achieved by using Ceratophyllum demersum L. - a well-known floating macrophyte. In vitro regenerated plants of C. demersum (7.5 g/L) were exposed to 24, 72, and 120 h to 0, 0.5, 1.0, 2.0, and 4.0 mg/L of cadmium (CdSO4·8H2O) in water. Results revealed significantly different relationship in terms of Cd in water, Cd uptake by plants, bioconcentration factor (BCF), and Cd removal (%) from water. The study showed that Cd uptake by plants and BCF values increased significantly with exposure time. The highest BCF value (3776.50) was recorded for plant samples exposed to 2 mg/L Cd for 72 h. Application of all Cd concentrations and various exposure duration yielded Cd removal (%) between the ranges of 93.8 and 98.7%. These results were predicted through artificial intelligence-based models, namely, random forest (RF), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). The tested models predicted the results accurately, and the attained results were further validated via three different performance metrics. The optimal regression coefficient (R2) for the models was recorded as 0.7970 (Cd water, mg/L), 0.9661 (Cd plants, mg/kg), 0.9797 bioconcentration factor (BCF), and 0.9996 (Cd removal, %), respectively. These achieved results suggest that in vitro regenerated C. demersum can be efficaciously used for phytoremediation of Cd-contaminated aquatic environments. Likewise, the proposed modeling of phytoremediation studies can further be employed more comprehensively in future studies aimed at data prediction and optimization.

TiO2 nanoparticle synthesis, characterization and application to shoot regeneration of water hyssop (Bacopa monnieri L. Pennel) in vitro.

Water hyssop (Bacopa monnieri L. Pennel) is a medicinal aquatic herb used to treat diseases in South Asia. Various regeneration protocols have been developed or modified in vitro to ensure the availability of biomass and secondary metabolites of Bacopa. We applied hydrothermally treated titanium dioxide (TiO2) nanoparticles (NPs) (TiO2-NPs) at different concentrations. Three explants, distal portion of half leaf (DPHL), proximal portion of half leaf (PPHL) and full leaf (FL), were used to evaluate response to TiO2. Regeneration from the three explants in vitro was similar except for shoot length. Application of TiO2-NPs exerted significant, but variable, effects on all parameters except percentage of shoot formation, which was 100%. Interactive effects of explant and TiO2-NPs exhibited significant, but variable, effects on fresh weight and percentage of callus formation. All explants produced more shoots using TiO2-NPs compared to control treatments. DPHL explants with application of 8 mg/l TiO2 produced more shoots than controls. Similarly, FL explant treated with 2 mg/l TiO2-NPs produced more shoots/explant than controls. All concentrations of TiO2-NPs produced significantly longer shoots compared to controls. Increased elongation of shoots justifies use of TiO2-NPs for propagation of plants in vitro during acclimatization. Use of TiO2-NPs for rapid elongation of shoots ultimately fosters survival of plants.

Delphinium uncinatum mediated biosynthesis of zinc oxide nanoparticles and in-vitro evaluation of their antioxidant, cytotoxic, antimicrobial, anti-diabetic, anti-inflammatory, and anti-aging activities.

Nanotechnology is perhaps the most widely explored scientific domain in the current era. With the advent of NPs, revolutionary changes have been observed in various scientific disciplines. Among the NPs, ZnO-NPs are the center of contemplation owing to their biocompatible nature. These nanoparticles have been prepared using a number of techniques; however, biological methods are among the most popular synthesis approaches. The current research therefore reports the phyto-fabrication of ZnO-NPs mediated by Delphinium uncinatum root extract. The resulting NPs were subjected to standard characterization methods such fourier transformed infrared spectroscopy, X-ray diffraction and transmission electron microscopy. The resulting NPs are exploited to their possible antioxidant, antimicrobial, antidiabetic, cytotoxic, anti-inflammatory and anti-ageing potency. FTIR confirmed the capping of ZnO-NPs by a variety of phytochemicals. ZnO-NPs average size was approximately 30 nm. ZnO-NPs exhibited substantial bio-potency and proved to be highly biocompatible even at higher concentrations. ZnO-NPs revealed strong antimicrobial potency for Pseudomonas aeruginosa proving to be the most susceptible strain showing inhibition of 16 ± 0.98. ZnO-NPs also showed dose dependent antidiabetic and cytotoxic potential. COX-1, COX-2, 15-LOX and sPLA2 were efficiently inhibited upon exposure to ZnO-NPs confirming the anti-inflammatory potential of ZnO-NPs. Similarly, ZnO-NPs also revealed considerable anti-aging potential. With such diverse biological potentials, ZnO-NPs can prove to be a potent weapon against a plethora of diseases; however, further study is necessary in order to discover the precise mechanism that is responsible for the biological potency of these NPs.

Recent advancement in OMICS approaches to enhance abiotic stress tolerance in legumes.

The world is facing rapid climate change and a fast-growing global population. It is believed that the world population will be 9.7 billion in 2050. However, recent agriculture production is not enough to feed the current population of 7.9 billion people, which is causing a huge hunger problem. Therefore, feeding the 9.7 billion population in 2050 will be a huge target. Climate change is becoming a huge threat to global agricultural production, and it is expected to become the worst threat to it in the upcoming years. Keeping this in view, it is very important to breed climate-resilient plants. Legumes are considered an important pillar of the agriculture production system and a great source of high-quality protein, minerals, and vitamins. During the last two decades, advancements in OMICs technology revolutionized plant breeding and emerged as a crop-saving tool in wake of the climate change. Various OMICs approaches like Next-Generation sequencing (NGS), Transcriptomics, Proteomics, and Metabolomics have been used in legumes under abiotic stresses. The scientific community successfully utilized these platforms and investigated the Quantitative Trait Loci (QTL), linked markers through genome-wide association studies, and developed KASP markers that can be helpful for the marker-assisted breeding of legumes. Gene-editing techniques have been successfully proven for soybean, cowpea, chickpea, and model legumes such as Medicago truncatula and Lotus japonicus. A number of efforts have been made to perform gene editing in legumes. Moreover, the scientific community did a great job of identifying various genes involved in the metabolic pathways and utilizing the resulted information in the development of climate-resilient legume cultivars at a rapid pace. Keeping in view, this review highlights the contribution of OMICs approaches to abiotic stresses in legumes. We envisage that the presented information will be helpful for the scientific community to develop climate-resilient legume cultivars.

Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms.

Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R 2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans.

Genome-wide in silico identification and characterization of the stress associated protein (SAP) gene family encoding A20/AN1 zinc-finger proteins in potato (Solanum tuberosum L.).

Stress associated proteins (SAPs) in plants have a key role in providing tolerance to multiple abiotic stresses. SAP gene family in Solanum tuberosum has not been fully studied before. This study identified 17 StSAP genes in S. tuberosum which code for A20/AN1 zinc-finger proteins. All the genes were distributed on ten different chromosomes and six segmental duplication events were identified. The SAPs in S. tuberosum and its orthologs in Arabidopsis thaliana were classified into six groups through the phylogenetic analysis. Introns across StSAP genes were identified in four genes. The promotor study of the StSAP genes showed different hormone and stress-related cis-elements that could potentially have a role in environmental stress response. The expression of StSAP genes in response to heat, mannitol, and salt were analyzed through in silico transcriptomic analysis. This study could potentially help in further understanding the functions of SAP genes in S. tuberosum.

α-Glucosidase, α-Amylase and Antioxidant Evaluations of Isolated Bioactives from Wild Strawberry.

Diabetes mellitus is a metabolic disorder and is a global challenge to the current medicinal chemists and pharmacologists. This research has been designed to isolate and evaluate antidiabetic bioactives from Fragaria indica. The crude extracts, semi-purified and pure bioactives have been used in all in vitro assays. The in vitro α-glucosidase, α-amylase and DPPH free radical activities have been performed on all plant samples. The initial activities showed that ethyl acetate (Fi.EtAc) was the potent fraction in all the assays. This fraction was initially semi-purified to obtain Fi.EtAc 1-3. Among the semi-purified fractions, Fi.EtAc 2 was dominant, exhibiting potent IC50 values in all the in vitro assays. Based on the potency and availability of materials, Fi.EtAc 2 was subjected to further purification to obtain compounds 1 (2,4-dichloro-6-hydroxy-3,5-dimethoxytoluene) and 2 (2-methyl-6-(4-methylphenyl)-2-hepten-4-one). The two isolated compounds were characterized by mass and NMR analyses. The compounds 1 and 2 showed excellent inhibitions against α-glucosidase (21.45 for 1 and 15.03 for 2 µg/mL), α-amylase (17.65 and 16.56 µg/mL) and DPPH free radicals (7.62 and 14.30 µg/mL). Our study provides baseline research for the antidiabetic bioactives exploration from Fragaria indica. The bioactive compounds can be evaluated in animals-based antidiabetic activity in future.

Deciphering the iPBS retrotransposons based genetic diversity of nanoparticles induced in Vitro seedlings of industrial hemp (Cannabis sativa L.).

BACKGROUND: The phytochemicals contained in hemp are highly significant and can be modified or altered by employing in vitro elicitors like nanoparticles (NPs). Application of NPs type, concentration, and treatment time regulate the germination, growth, and phytohemicals. METHODS AND RESULTS: In vitro sterilized seeds of cannabis were augmented on Murashige and Skoog (MS) medium supplemented with silver (Ag) and titanium dioxide (TiO2) nanoparticles at different concentrations (0, 200, 400, 800, 1200 and 1600 mg/L) for one month. Results revealed that supplementation of NPs resulted in reduced germination (%), root length and longer shoots and seedling fresh wt compared to control. CONCLUSIONS: Maximum germination was recorded on MS medium supplemented with 1600 mg/L TiO2NPs (92.50%) followed by 1600 mg/L AgNPs (80.00%). Supplementation of 800 mg/L AgNPs yielded longer shoots, roots, seedlings fresh weight, and chlorophyll-b contents compared to all other treatments. Whereas, maximum chlorophyll-a, carotenoids, and MDA contents were attributed to 1200 mg/L TiO2NPs. PCR results using eight iPBS-retrotransposons primers yielded a total of 101 bands with 98 polymorphic bands. Whereas, minimum (0.28) and maximum (0.42) gene diversity was associated with 2095 and 2228 primers.

Sociodemographic and genetic determinants of nonalcoholic fatty liver disease in type 2 diabetes mellitus patients.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) showed significant association with PNPLA3 rs738409 polymorphism in unrelated individuals. However, it is still unknown whether the relationship of NAFLD with PNPLA3 variant exists or not among subjects with type 2 diabetes mellitus (T2DM). Therefore, the study aimed to evaluate sociodemographic and genetic determinants of NAFLD in type 2 diabetics. METHODS: The cross-sectional analytical study was conducted at the Department of Molecular Biology, Virtual University of Pakistan, Lahore, Pakistan, during 2019-2020. A total of 153 known cases of T2DM were enrolled using convenience sampling. After excluding patients (n = 24) with HCV, alcoholism, or missing information, data from 129 eligible diabetics with and without NAFLD were analyzed using SPSS. Odds ratios using crosstabs and adjusted odds ratios using binary and multinomial logistic regression were calculated to measure the risk of NAFLD. RESULTS: Adults 18-35 years were 7.0%, 36-55 years were 64.3%, ≥ 56 years were 28.7%, and females were 66.7%. A total of 41.1% of patients had obesity, 52.7% had NAFLD, and 29.05% carried mutant G allele of rs738409 polymorphism. Among overall diabetics, NAFLD showed association with female (OR = 2.998, p = 0.007), illiterate (OR = 3.067, p = 0.005), and obese (OR = 2.211, p = 0.046) but not with PNPLA3 genotype under any model (all p = > 0.05). Among obese diabetics, NAFLD showed association with female (AOR = 4.010, p = 0.029), illiterate (AOR = 3.506, p = 0.037), GG + CG/CC (AOR = 3.303, p = 0.033), and GG/CG + CC (AOR = 4.547, p = 0.034) using binary regression and with female (AOR = 3.411, p = 0.051), illiterate (AOR = 3.323, p = 0.048), GG + CG/CC (AOR = 3.270, p = 0.029), and GG/CG + CC (AOR = 4.534, p = 0.024) using multinomial regression. CONCLUSIONS: NAFLD and obesity were the most common comorbid diseases of T2DM. Gender female, being illiterate, and PNPLA3 rs738409 polymorphism were significant risk factors of NAFLD among obese diabetic patients.

Frequency of non-alcoholic fatty liver disease (NAFLD) and its associated risk factors among Type-2 diabetics.

OBJECTIVES: To determine the frequency of Non-Alcoholic Fatty Liver Disease (NAFLD) and its associated risk factors among Type-2 Diabetic patients. METHODS: This cross-sectional study was conducted in Diabetic Clinic of Shaikh Zayed Postgraduate Medical Institute Lahore from September 2019-February 2020. Type-2 diabetics regardless of age were divided into two groups, one with fatty liver disease and the other without this, evaluated by Abdominal Ultrasonography and were further evaluated by measurement of BMI, obesity, HbA1c and lipid profile. Exclusion criteria were patients having history of or currently taking alcohol, chronic Liver Disease of any cause and intake of hepatotoxic drugs. Qualitative measures were compared between groups by using Chi-square test. Binary logistic regression was used to see the association of factors with fatty liver disease. P-value ≤ 0.05 was considered significant. RESULTS: A total of 185 subjects were included in the study with the mean age of 53.0±9.0 years. About 54.6% patients were diagnosed to have fatty liver disease. When compared the cases with and without fatty liver disease, age and HDL cholesterol had no significant difference between groups while other measures like BMI, TGs & cholesterol levels, ALT and AST were significantly higher among cases with NAFLD. BMI >24.5, HbA1c >7.0 and ALT >40.0 can predict NAFLD among Type-2 diabetic patients with 96.8% accuracy. CONCLUSION: There is high prevalence of NAFLD among Type-2 diabetic patients and strong association between Type-2 diabetics with NAFLD and risk factors like; obesity, high HbA1c, hyperlipidemia and high ALT. Therefore, early recognition by ultrasonography in high risk patients and intervention like life style modification, maintenance of healthy weight, obesity prevention, treatment of dyslipidemia and good glycemic control should be achieved in such subjects and can prevent NAFLD.