The intercalated cells of the kidney collecting duct are specialized for physiologically regulated proton transport. In these cells, a vacuolar H+-ATPase is expressed at enormous levels in a polarized distribution on the plasma membrane, enabling it to serve in transepithelial H+ transport. In contrast, in most eukaryotic cells, vacuolar H+-ATPases reside principally in intracellular compartments to effect vacuolar acidification. To investigate the basis for the selective amplification of the proton pump in intercalated cells, we isolated and sequenced cDNA clones for two isoforms of the -56-kDa subunit of the H+-ATPase and examined their expression in various tissues. The predicted amino acid sequence of the isoforms was highly conserved in the internal region but diverged in the amino and carboxyl termini. mRNA hybridization to a cDNA probe for one isoform (the "kidney" isoformn) was detected only in kidney cortex and medulla, whereas mRNA hybridization to the other isoform of the -56-kDa subunit and to the H+-ATPase 31-kDa subunit was found in the kidney and other tissues. Immunocytochemistry of rat kidney with an antibody specific to the kidney isoform revealed intense staining only in the intercalated cells. Staining was absent from proximal tubule and thick ascending limb, where H+-ATPase was detected with a monoclonal antibody to the 31-kDa subunit of the H+-ATPase. This example ofspecific amplification ofan isoform of one subunit of the vacuolar H+-ATPase being limited to a specific cell type suggests that the selective expression of the kidney isoform of the -56-kDa subunit may confer the capacity for amplification and other specialized functions of the vacuolar H+-ATPase in the renal intercalated cell.Vacuolar H+-ATPases participate in a remarkably diverse variety of cellular functions. In the intracellular membrane compartments of eukaryotic cells, they acidify endosomes, lysosomes, and other components of the vacuolar system, serving in endocytosis and secretion (1). In cells specialized for H' transport, such as the renal intercalated cell (2, 3) and the osteoclast (4), vacuolar H+-ATPases reside in high densities in a polarized distribution on the plasma membrane, effecting transcellular proton transport. How the vacuolar class of H+-ATPases performs such diverse functions remains unknown. Accumulating evidence suggests that structural subsets of the vacuolar H+-ATPases exist that may have unique roles. In prior studies, we reported that a vacuolar H+-ATPase preparation isolated from bovine kidney microsomes could be resolved on an HPLC ion-exchange column as two peaks of activity that exhibited differences in the structure of their -56-kDa subunits on SDS/polyacrylamide gels (5). More recently, we found that H+-ATPase purified from different membrane compartments in the mammalian kidney varied in their structural and functional properties (6). Again, differences in the structure ofthe -56-kDa polypeptide subunit were noted. Work from several laboratories has subsequently revealed at least ...

To understand astrocyte-specific transcription, we have been studying the human gfa gene. This gene encodes glial fibrillary acidic protein (GFAP), an intermediate filament protein expressed primarily in astrocytes. A survey of the gfa 5' flanking region showed it to contain several segments that contribute to expression of a chloramphenicol acetyltransferase reporter gene in transfected cells. The most active of these was the 124-bp B region, which spans bp -1612 to -1489. We have now used site-directed mutagenesis to analyze this region in greater detail, and show that the B region itself contains several important elements. The most crucial of these is a consensus AP-1 sequence, the binding site for the Fos and Jun families of transcription factors. The presence of members of both these families in the glial fibrillary acidic protein-expressing U251 cell line used for our transfection studies was verified by gel mobility-shift experiments. This is the first demonstration of the functioning of a specific transcription factor site for astrocytes, and provides a focus for future studies of glial fibrillary acidic protein regulation during development and reactive gliosis.

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We have isolated a cDNA encoding the 31-kDa subunit of the bovine kidney vacuolar H+-ATPase. The composite sequence contains 1219 base pairs, which includes the entire 678-base-pair coding region. A lysine-rich sequence previously found in the Na',K+-ATPase a subunit and the H+,K+-ATPase was identified in the 31-kDa subunit. An Proton-translocating ATPases acidify a variety of intracellular compartments in the vacuolar system (1). In the specialized acid-secreting kidney intercalated cell, the vacuolar H+-ATPase (proton pump) is also found in high concentrations on the plasma membrane, where its polarized distribution effects transepithelial proton secretion (2). Recently, this laboratory reported the isolation and functional reconstitution of the vacuolar H+-ATPase from bovine kidney microsomes (3, 4). The intact purified enzyme has a molecular mass of =580 kDa and has over 10 component subunits [i.e., one each of 70, 45, 42, 38, 33, 31, 15, 14, and 12 kDa and several of -56 kDa (3, 4)].Vacuolar proton pumps partially purified from Neurospora vacuoles (5), plant tonoplast (6, 7), chromaffin granules (8), and coated vesicles (9) also are large molecular mass enzymes with subunits of t70, =56, -17 and, generally, -30 kDa (5,6,8,9). Several features suggest that the complex structure of these enzymes and of the kidney H +-ATPase is similar to that of FoF1 H + -ATPases, such as the mitochondrial H + -ATPase. Rapid-freeze and thinsection electron micrographs of the vacuolar H+-ATPase show a 9.5-nm cytoplasmic domain ("stud") bound to the membrane (10), which is morphologically similar to FoF, ATPase structures. Antibodies specific for the 70-, 56-, or 31-kDa kidney H+-ATPase subunits all localize to this cytoplasmic domain (37). The %70-(5) and -56-kDa (7) subunits have been implicated in the enzyme's catalytic activity, whereas the dicyclohexylcarbodiimide-binding '17-kDa subunit (5, 7) may form part of an integral membrane channel.The cytosolic domains of several membrane proteins are necessary for sorting and control of removal by endocytosis (11,12). The H+-ATPase's cytoplasmic domain might, in addition to having a role in catalytic activity, function in enzyme regulation or sorting to different membrane com-

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Potato leaf disease detection in an early stage is challenging because of variations in crop species, crop diseases symptoms and environmental factors. These factors make it difficult to detect potato leaf diseases in the early stage. Various machine learning techniques have been developed to detect potato leaf diseases. However, the existing methods cannot detect crop species and crop diseases in general because these models are trained and tested on images of plant leaves of a specific region. In this research, a multi-level deep learning model for potato leaf disease recognition has developed. At the first level, it extracts the potato leaves from the potato plant image using the YOLOv5 image segmentation technique. At the second level, a novel deep learning technique has been developed using a convolutional neural network to detect the early blight and late blight potato diseases from potato leaf images. The proposed potato leaf disease detection model was trained and tested on a potato leaf disease dataset. The potato leaf disease dataset contains 4062 images collected from the Central Punjab region of Pakistan. The proposed deep learning technique achieved 99.75% accuracy on the potato leaf disease dataset. The performance of the proposed techniques was also evaluated on the PlantVillage dataset. The proposed technique is also compared with the state-of-the-art models and achieved significantly concerning the accuracy and computational cost.

The purpose of this research was to provide a “systematic literature review” of knee bone reports that are obtained by MRI, CT scans, and X-rays by using deep learning and machine learning techniques by comparing different approaches—to perform a comprehensive study on the deep learning and machine learning methodologies to diagnose knee bone diseases by detecting symptoms from X-ray, CT scan, and MRI images. This study will help those researchers who want to conduct research in the knee bone field. A comparative systematic literature review was conducted for the accomplishment of our work. A total of 32 papers were reviewed in this research. Six papers consist of X-rays of knee bone with deep learning methodologies, five papers cover the MRI of knee bone using deep learning approaches, and another five papers cover CT scans of knee bone with deep learning techniques. Another 16 papers cover the machine learning techniques for evaluating CT scans, X-rays, and MRIs of knee bone. This research compares the deep learning methodologies for CT scan, MRI, and X-ray reports on knee bone, comparing the accuracy of each technique, which can be used for future development. In the future, this research will be enhanced by comparing X-ray, CT-scan, and MRI reports of knee bone with information retrieval and big data techniques. The results show that deep learning techniques are best for X-ray, MRI, and CT scan images of the knee bone to diagnose diseases.

, and non-Hodgkin lymphoma (NHL, 9.53%) were found to be the highest in male patients, whereas breast cancer (46.7%), ovary tumors (6.80%), and cervix (6.31%) cancer incidence rates were observed to be the most common in female patients. The age range distribution of diagnosed and treated patients in conjunction with the percentage contribution of cancer patients from 15 different cities of Punjab province treated at the Institute of Nuclear Medicine and Oncology, Lahore are also included. Leukemia was found to be the most common cancer for the age group of 1-12 years. It has been identified that the maximum number of diagnosed cases were found in the age range of 51-60 years for males and 41-50 years for female cancer patients. Conclusions: Overall cancer incidence of the thirty years demonstrated that head and neck and breast cancers in males and in females respectively are the most common cancers in Punjab province in Pakistan, at rates almost the highest in Asia, requiring especial attention. The incidence of brain, NHL, and prostate cancers among males and ovarian and cervix cancers among females have increased rapidly. These data from a major population of Punjab province should be helpful for implementation of appropriate planning, prevention and cancer control measures and for determination of risk factors within the country.