Date palm pollen (DPP) plays a very important role in the fertilization process, since its viability and the pollination method influence on the quality, development, and yield of the fruit. In the present study, a broad review of its main characteristics, consumption, and DPP production are presented, as well as a description of its extraction methods and viability tests. The evolution of the pollination methods used in the date palm is also presented, from its natural pollination to the use of specialized mechanical and electrical devices, as well as the use of dry DPP and the current trend towards the use of DPP in liquid suspension. Likewise, the efficiency of the methods of natural pollination (wind); traditional (strands placement); dusting hand; dusting with manual, mechanical, or electric pollinator; and liquid pollination were evaluated from the fruit set percentage (FSP). Finally, starting from a scientometric analysis, the pollination methods were widely discussed, concluding that the dusting spraying of pollen suspension with liquid DPP is the pollination method that commonly presents the highest FSP, followed by dusting dry DPP with a motorized pollinator.

Type 2 diabetes (T2D) is a chronic systemic disease with a complex etiology, characterized by insulin resistance and mitochondrial dysfunction in various cell tissues. To explore this relationship, we conducted a secondary analysis of complete mtDNA sequences from 1261 T2D patients and 1105 control individuals. Our findings revealed significant associations between certain single-nucleotide polymorphisms (SNPs) and T2D. Notably, the variants m.1438A>G (rs2001030) (controls: 32 [27.6%], T2D: 84 [72.4%]; OR: 2.46; 95%CI: 1.64–3.78; p < 0.001), m.14766C>T (rs193302980) (controls: 498 [36.9%], T2D: 853 [63.1%]; OR: 2.57, 95%CI: 2.18–3.04, p < 0.001), and m.16519T>C (rs3937033) (controls: 363 [43.4%], T2D: 474 [56.6%]; OR: 1.24, 95%CI: 1.05–1.47, p = 0.012) were significantly associated with the likelihood of developing diabetes. The variant m.16189T>C (rs28693675), which has been previously documented in several studies across diverse populations, showed no association with T2D in our analysis (controls: 148 [13.39] T2D: 171 [13.56%]; OR: 1.03; 95%CI: 0.815–1.31; p = 0.83). These results provide evidence suggesting a link between specific mtDNA polymorphisms and T2D, possibly related to association rules, topological patterns, and three-dimensional conformations associated with regions where changes occur, rather than specific point mutations in the sequence.

CdS, CdTe, Hg_0.1Cd_0.9Te, CdTe, and Ag films were progressively electrodeposited on ITO-coated soda–lime glass to manufacture a short- and mid-wavelength infrared photodetector. A distinctive feature of the applied electrodeposition method is the use of a non-aqueous solution containing ethylene glycol (EG) as the electrolyte in a traditional three-electrode configuration for every film deposition. Using EG as a supplementary electrolyte and using the same deposition conditions with a potential below 0.75 V for all film coatings reduces their environmental incompatibility and offers a low-cost and low-energy route for fabricating the reported photodetector. The produced photodetector has a sensitivity of up to ≈957 nm with a detectivity (D*) of 2.86 × 10¹² cm Hz^1/2 W⁻¹ and a dark current density (J_dark) of 10⁻⁶ mA cm⁻². Furthermore, the manufactured photodiode exhibits self-powered performance because V_oc and J_sc are self-generated, unlike previously reported photodiodes. The presented all-layer electrodeposition assembly approach can easily be adapted to fabricate sensing devices for different applications.

Hypoplasia and ovarian cysts are the most common ovarian pathologies in cattle. In this genome-wide study we analyzed the signal intensity of 648,315 Single Nucleotide Polymorphisms (SNPs) and identified 1338 genes differentiating cows with ovarian pathologies from healthy cows. The sample consisted of six cows presenting an ovarian pathology and six healthy cows. SNP signal intensities were measured with a genotyping process using the Axiom Genome-Wide BOS 1 SNPchip. Statistical tests for equality of variance and mean were applied to SNP intensities, and significance p-values were obtained. A Benjamini-Hochberg multiple testing correction reveled significant SNPs. Corresponding genes were identified using the Bovine Genome UMD 3.1 annotation. Principal Components Analysis (PCA) confirmed differentiation. An analysis of Copy Number Variations (CNVs), obtained from signal intensities, revealed no evidence of association between ovarian pathologies and CNVs. In addition, a haplotype frequency analysis showed no association with ovarian pathologies. Results show that SNP signal intensity, which captures not only information for base-pair genotypes elucidation, but the amount of fluorescence nucleotide synthetization produced in an enzymatic reaction, is a rich source of information that, by itself or in combination with base-pair genotypes, might be used to implement differentiation, prediction and diagnostic procedures, increasing the scope of applications for Genotyping Microarrays.

Diabetes Mellitus Type 2 (DM2) is a complex and multifaceted disorder currently listed as one of the epidemics of the twenty-first century due to its prevalence and the adverse cardiovascular effects it causes. This chapter examines the relationships between base-pair positions in human mitochondrial genome and type 2 diabetes. The data included 510 complete mitochondrial genomes, of which 437 belonged to individuals with type 2 diabetes and 73 to healthy individuals. An alignment algorithm allowed inspecting and choosing a region with optional positions for analysis, a principal component analysis permitted viewing the data structure, and after a regression analysis, we declared three base-pair positions associated to DM2. Upon examination of the genome annotation, three genes were identified as potential candidates for association, one of which was previously linked to type 2 diabetes according to previous studies. This chapter offers further proof of a possible genetic link between type 2 diabetes and metabolic syndrome.

Lasers with external electrical modulation are widely used in optical systems, but the generation of well-defined pulses often suffers from distortions in duty cycle and top optical power at high frequencies. This work addresses this limitation by presenting an automated setup for optical pulse correction that combines standard instrumentation with a feedback-based adjustment strategy. The system integrates a continuous-wave laser, a signal generator, an optical analyzer, and a control routine implemented in MATLAB (R2024b Campus Wide). Two nested loops are employed; the inner loop varies the amplitude of a sinusoidal modulation signal to regulate the duty cycle at the desired reference; the outer loop sends commands to the laser to adjust optical power level to a specified reference. Experimental validation shows that the proposed approach significantly improves pulse fidelity over a frequency range up to 100 MHz. In particular, the relative normalized root mean square error (NRMSE) was reduced by more than 97% compared with the case without adjustment, both for duty cycle (1–30 MHz) and top optical power (10–30 MHz). These results demonstrate that precise optical pulse control can be implemented with common laboratory instrumentation, providing a practical and accessible solution for automated pulse conditioning in externally modulated laser setups.