Molecular physiology for the increase of soluble sugar accumulation in citrus fruits under drought stress.

To investigate the mechanism for drought promoting soluble sugar accumulation will be conducive to the enhancement of citrus fruit quality as well as stress tolerance. Fruit sucrose mainly derives from source leaves. Its accumulation in citrus fruit cell vacuole involves in two processes of unloading in the fruit segment membrane (SM) and translocating to the vacuole of fruit juice sacs (JS). Here, transcript levels of 47 sugar metabolism- and transport-related genes were compared in fruit SM or JS between drought and control treatments. Results indicated that transcript levels of cell wall invertase genes (CwINV2/6) and sucrose synthase genes (SUS2/6) in the SM were significantly increased by the drought. Moreover, transcript levels of SWEET genes (CsSWEET1/2/4/5/9) and monosaccharide transporter gene (CsPMT3) were significantly increased in SM under drought treatment. On the other hand, SUS1/3 and vacuolar invertase (VINV) transcript levels were significantly increased in JS by drought; CsPMT4, sucrose transporter gene 2 (CsSUT2), tonoplast monosaccharide transporter gene 2 (CsTMT2), sugar transport protein gene 1 (CsSTP1), two citrus type I V-PPase genes (CsVPP1, and CsVPP2) were also significantly increased in drought treated JS. Collectively, the imposition of drought stress resulted in more soluble sugar accumulation through enhancing sucrose download by enhancing sink strength- and transport ability-related genes, such as CwINV2/6, SUS2/6, CsSWEET1/2/4/5/9, and CsPMT3, in fruit SM, and soluble sugar storage ability by increasing transcript levels of genes, such as CsPMT4, VINV, CsSUT2, CsTMT2, CsSTP1, CsVPP1, and CsVPP2, in fruit JS.

Brain Tumor Classification from MRI Using Image Enhancement and Convolutional Neural Network Techniques.

The independent detection and classification of brain malignancies using magnetic resonance imaging (MRI) can present challenges and the potential for error due to the intricate nature and time-consuming process involved. The complexity of the brain tumor identification process primarily stems from the need for a comprehensive evaluation spanning multiple modules. The advancement of deep learning (DL) has facilitated the emergence of automated medical image processing and diagnostics solutions, thereby offering a potential resolution to this issue. Convolutional neural networks (CNNs) represent a prominent methodology in visual learning and image categorization. The present study introduces a novel methodology integrating image enhancement techniques, specifically, Gaussian-blur-based sharpening and Adaptive Histogram Equalization using CLAHE, with the proposed model. This approach aims to effectively classify different categories of brain tumors, including glioma, meningioma, and pituitary tumor, as well as cases without tumors. The algorithm underwent comprehensive testing using benchmarked data from the published literature, and the results were compared with pre-trained models, including VGG16, ResNet50, VGG19, InceptionV3, and MobileNetV2. The experimental findings of the proposed method demonstrated a noteworthy classification accuracy of 97.84%, a precision success rate of 97.85%, a recall rate of 97.85%, and an F1-score of 97.90%. The results presented in this study showcase the exceptional accuracy of the proposed methodology in accurately classifying the most commonly occurring brain tumor types. The technique exhibited commendable generalization properties, rendering it a valuable asset in medicine for aiding physicians in making precise and proficient brain diagnoses.

Advancements in Neighboring-Based Energy-Efficient Routing Protocol (NBEER) for Underwater Wireless Sensor Networks.

Underwater wireless sensor networks (UWSNs) have gained prominence in wireless sensor technology, featuring resource-limited sensor nodes deployed in challenging underwater environments. To address challenges like power consumption, network lifetime, node deployment, topology, and propagation delays, cooperative transmission protocols like co-operative (Co-UWSN) and co-operative energy-efficient routing (CEER) have been proposed. These protocols utilize broadcast capabilities and neighbor head node (NHN) selection for cooperative routing. This research introduces NBEER, a novel neighbor-based energy-efficient routing protocol tailored for UWSNs. NBEER aims to surpass the limitations of Co-UWSN and CEER by optimizing NHNS and cooperative mechanisms to achieve load balancing and enhance network performance. Through comprehensive MATLAB simulations, we evaluated NBEER against Co-UWSN and CEER, demonstrating its superior performance across various metrics. NBEER significantly maximizes end-to-end delay, reduces energy consumption, improves packet delivery ratio, extends network lifetime, and enhances total received packets analysis compared to the existing protocols.

Novel Variants in MPV17, PRX, GJB1, and SACS Cause Charcot-Marie-Tooth and Spastic Ataxia of Charlevoix-Saguenay Type Diseases.

Charcot-Marie-Tooth disease (CMT) and autosomal recessive spastic ataxia of Charlevoix-Saguenay type (ARSACS) are large heterogeneous groups of sensory, neurological genetic disorders characterized by sensory neuropathies, muscular atrophies, abnormal sensory conduction velocities, and ataxia. CMT2EE (OMIM: 618400) is caused by mutations in MPV17 (OMIM: 137960), CMT4F (OMIM: 614895) is caused by PRX (OMIM: 605725), CMTX1 (OMIM: 302800) is caused by mutations in GJB1 (OMIM: 304040), and ARSACS (OMIM: 270550) is caused by mutations in SACS (OMIM: 604490). In this study, we enrolled four families: DG-01, BD-06, MR-01, and ICP-RD11, with 16 affected individuals, for clinical and molecular diagnoses. One patient from each family was analyzed for whole exome sequencing and Sanger sequencing was done for the rest of the family members. Affected individuals of families BD-06 and MR-01 show complete CMT phenotypes and family ICP-RD11 shows ARSACS type. Family DG-01 shows complete phenotypes for both CMT and ARSACS types. The affected individuals have walking difficulties, ataxia, distal limb weakness, axonal sensorimotor neuropathies, delayed motor development, pes cavus, and speech articulations with minor variations. The WES analysis in an indexed patient of family DG-01 identified two novel variants: c.83G>T (p.Gly28Val) in MPV17 and c.4934G>C (p.Arg1645Pro) in SACS. In family ICP-RD11, a recurrent mutation that causes ARSACS, c.262C>T (p.Arg88Ter) in SACS, was identified. Another novel variant, c.231C>A (p.Arg77Ter) in PRX, which causes CMT4F, was identified in family BD-06. In family MR-01, a hemizygous missense variant c.61G>C (p.Gly21Arg) in GJB1 was identified in the indexed patient. To the best of our knowledge, there are very few reports on MPV17, SACS, PRX, and GJB1 causing CMT and ARSACS phenotypes in the Pakistani population. Our study cohort suggests that whole exome sequencing can be a useful tool in diagnosing complex multigenic and phenotypically overlapping genetic disorders such as Charcot-Marie-Tooth disease (CMT) and spastic ataxia of Charlevoix-Saguenay type.

A Novel Design and Development of a Strip-Fed Circularly Polarized Rectangular Dielectric Resonator Antenna for 5G NR Sub-6 GHz Band Applications.

In this article, a rectangular dielectric resonator antenna (RDRA) with circularly polarized (CP) response is presented for 5G NR (New Radio) Sub-6 GHz band applications. A uniquely shaped conformal metal feeding strip is proposed to excite the RDRA in higher-order mode for high gain utilization. By using the proposed feeding mechanism, the degenerate mode pair of the first higher-order, i.e., TEδ13x at 4.13 GHz and TE1δ3y, at 4.52 GHz is excited to achieve a circularly polarized response. A circular polarization over a bandwidth of ~10%, in conjunction with a wide impedance matching over a bandwidth of ~17%, were attained by the antenna. The CP antenna proposed offers a useful gain of ~6.2 dBic. The achieved CP bandwidth of the RDRA is good enough to cover the targeted 5G NR bands around 4.4−4.8 GHz, such as n79. The proposed antenna configuration is modelled and optimized using computer simulation technology (CST). A prototype was built to confirm (validate) the performance estimated through simulation. A good agreement was observed between simulated and measured results.

High Performance Eight-Port Dual-Band MIMO Antenna System for 5G Devices.

This study provides an eight-component multiple-input multiple-output (MIMO) antenna architecture for fifth-generation (5G) mobile communication systems. The single antenna element is comprised of an L-shaped radiating component, an L-shaped parasitic element, and a ground plane with a rectangular slot. The main element with a slot-loaded ground plane helps to draw current from a coaxial feed from the other side of the board, while the parasitic element helps to elongate the current path and improve the impedance of the system. This enables the system to radiate at two different frequency ranges: 3.34-3.7 GHz and 4.67-5.08 GHz, with 360 MHz and 410 MHz bandwidths, respectively. For MIMO configuration, the radiating elements are designed on either side of a 0.8 mm thick FR-4 substrate, allowing space to accommodate a battery, radio frequency (RF) systems and subsystems, and camera and sensor modules. The corner and the middle elements are arranged in such a manner so that they can provide spatial and pattern diversity. Furthermore, at least 12 dB of isolation is established between any two radiating elements. Various MIMO performance parameters were evaluated, e.g., mean effective gain (MEG), channel capacity (CC), envelope correlation coefficient (ECC), realized gain, far-field characteristics, and efficiency. Single- and double-hand mode evaluations were performed to further demonstrate the capability of the proposed MIMO antenna. A prototype of the proposed MIMO antenna was manufactured and assessed to verify the simulated data. The measured and simulated results were found to be in good agreement. On the basis of its performance characteristics, the designed MIMO system could be used in 5G communication systems.

On Improved 3D-CNN-Based Binary and Multiclass Classification of Alzheimer's Disease Using Neuroimaging Modalities and Data Augmentation Methods.

Alzheimer's disease (AD) is an irreversible illness of the brain impacting the functional and daily activities of elderly population worldwide. Neuroimaging sensory systems such as Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) measure the pathological changes in the brain associated with this disorder especially in its early stages. Deep learning (DL) architectures such as Convolutional Neural Networks (CNNs) are successfully used in recognition, classification, segmentation, detection, and other domains for data interpretation. Data augmentation schemes work alongside DL techniques and may impact the final task performance positively or negatively. In this work, we have studied and compared the impact of three data augmentation techniques on the final performances of CNN architectures in the 3D domain for the early diagnosis of AD. We have studied both binary and multiclass classification problems using MRI and PET neuroimaging modalities. We have found the performance of random zoomed in/out augmentation to be the best among all the augmentation methods. It is also observed that combining different augmentation methods may result in deteriorating performances on the classification tasks. Furthermore, we have seen that architecture engineering has less impact on the final classification performance in comparison to the data manipulation schemes. We have also observed that deeper architectures may not provide performance advantages in comparison to their shallower counterparts. We have further observed that these augmentation schemes do not alleviate the class imbalance issue.

MIMO Antenna System for Modern 5G Handheld Devices with Healthcare and High Rate Delivery.

In this work, a new prototype of the eight-element MIMO antenna system for 5G communications, internet of things, and networks has been proposed. This system is based on an H-shaped monopole antenna system that offers 200 MHz bandwidth ranges between 3.4-3.6 GHz, and the isolation between any two elements is well below -12 dB without using any decoupling structure. The proposed system is designed on a commercially available 0.8 mm-thick FR4 substrate. One side of the chassis is used to place the radiating elements, while the copper from the other side is being removed to avoid short-circuiting with other components and devices. This also enables space for other systems, sub-systems, and components. A prototype is fabricated and excellent agreement is observed between the experimental and the computed results. It was found that ECC is 0.2 for any two radiating elements which is consistent with the desirable standards, and channel capacity is 38 bps/Hz which is 2.9 times higher than 4 × 4 MIMO configuration. In addition, single hand mode and dual hand mode analysis are conducted to understand the operation of the system under such operations and to identify losses and/or changes in the key performance parameters. Based on the results, the proposed antenna system will find its applications in modern 5G handheld devices and internet of things with healthcare and high rate delivery. Besides that, its design simplicity will make it applicable for mass production to be used in industrial demands.

Assessment of sugar and sugar accumulation-related gene expression profiles reveal new insight into the formation of low sugar accumulation trait in a sweet orange (Citrus sinensis) bud mutant.

The accumulation of soluble sugars in fleshy fruits largely determines their sweetness or taste. A spontaneous sweet orange mutant 'Hong Anliu' (HAL, Citrus sinensis) accumulates low soluble sugar content in fruit juice sacs than its wild type, 'Anliu' (AL) orange; however, the cause of reduced sugar content in 'HAL' fruit remains unclear. In this study, sugar content and expression profiles of genes involved in sugar metabolism and transport were compared between 'HAL' and 'AL' fruit juice sacs. In both cultivars, fructose and glucose displayed the increasing trends with significantly lower contents in 'HAL' than 'AL' after 160 DAF; moreover, sucrose had a declining trend in 'HAL' and increasing trend in 'AL' with fruit development. On the other hand, transcript levels of VINV, CWINV1, CWINV2, SUS4, SUS5, SPS1, SPS2, VPP-1, VPP-2, and some sugar transporter genes were significantly decreased in 'HAL' compared with 'AL' after 100 DAF or 160 DAF. Interestingly, the transcript levels of SPS2 and SUT2 exhibited a similar trend as it was found for sucrose content in both cultivars. These results suggested that the low sugar accumulation in 'HAL' fruit JS is accompanied by the reduced sink strength, sucrose-synthesis ability, and vacuolar storage ability compared with 'AL'; reduction of CWINVs, VINV, SPS2, SUT2, VPP-1, and VPP-2 transcript levels possibly plays a key role in the low storage of soluble sugars in the vacuoles of mutant juice sacs.

CsPH8, a P-type proton pump gene, plays a key role in the diversity of citric acid accumulation in citrus fruits.

Citric acid homeostasis patterns and its content are diversified among the fruits of citrus cultivars, but the cause remained unclear. In this study we showed that changes of citric acid content were highly associated with the expression profiles of a P-type proton pump gene (CsPH8) in the fruits of six citrus cultivars; moreover, analysis of 21 different fruit samples indicated that the correlation coefficient between titratable acid content and CsPH8 transcript level was 0.5837 with a significant level (P < 0.05). Overexpression of CsPH8 in acidless pumelo juice sacs, strawberry fruit, and tomato fruit significantly increased the titratable acid or citric acid content besides the gene transcript level. On another hand, RNA interference of CsPH8 in acidic pumelo juice sacs significantly decreased the CsPH8 transcript level and the titratable acid or citric acid content as well. In addition, severe drought significantly increased the CsPH8 transcript level besides the titratable acid content. Taken together, these findings address the function of CsPH8 in citrus vacuolar acidification, confirm that CsPH8 plays a key role in the variation of citric acid content, and supported that the acid fluctuation influenced by drought, is at least partly due to the change of CsPH8 transcript level.