Primary amyloidosis of the conjunctiva and eyelid is a rare and often misdiagnosed condition. It is characterized by the deposition of insoluble amyloid fibrils, which are misfolded proteins, in the body. Amyloidosis can be systemic or localized with different types of amyloid fibril proteins identified using mass spectrometry. Ocular involvement in amyloidosis can lead to corneal dystrophies, glaucoma, vitreous opacities, and other symptoms. Diagnosis involves clinical examination and histopathological assessment. Treatment options depend on the extent of involvement and may include surgical excision, glaucoma management, vitrectomy, or liver transplantation in rare cases. We present a rare case of localized conjunctival amyloidosis initially misdiagnosed as pyogenic granuloma, with clinical symptoms of ptosis, periorbital swelling, and conjunctival lesions. The patient underwent excision of the lesions, and subsequent evaluation did not reveal systemic amyloidosis. Ocular amyloidosis requires careful diagnosis and consideration of systemic involvement for appropriate management.

Primary amyloidosis of the bladder is a rare clinical occurrence, with only a limited number of cases documented in literature thus far. Herein, is the presentation of a case involving a 75 year old male who presented with painless gross hematuria. Subsequent laboratory results and imaging completed were misleading, creating a high suspicion for bladder malignancy. Further workup revealed bladder biopsies to have positive apple-green birefringence with Congo-red immunostaining, diagnostic of amyloidosis.

The diagnosis of amyloidosis requires histological confirmation of Congo-red (CR) deposits. The tissue source is preferably fat aspiration and/or bone marrow (BM) biopsy, but at times organ biopsy is required.
We studied 612 patients with systemic immunoglobulin light chain amyloidosis to characterise the tissues used to establish the diagnosis.
The median number of tissue samples was 3. About 95% of BM biopsies were stained for CR, while 79% of patients had fat aspiration CR-stained. CR stain sensitivity was 69% in BM, 75% in fat aspiration and 89% for both sources combined. In comparison, CR sensitivity was 97-100% for heart, renal and liver biopsies. About 42% of patients with renal involvement, 21% of patients with liver involvement and 13% of patients with heart involvement underwent organ biopsy, when a less invasive biopsy would have established the diagnosis. Predictors for the requirement for organ biopsy were male sex, limited organ involvement and lack of fat aspiration.
Fat aspiration is underutilised for histologic confirmation of amyloidosis. A high rate of organ biopsies represents a failure to recognise the disease. Early awareness of amyloidosis in patients with organ dysfunction may lead to more judicious use of organ biopsies in this disease. Key messages Fat pad aspiration is underutilised to establish the diagnosis of amyloidosis. Bone marrow and fat pad aspiration obviates the need for invasive biopsies. The excessive use of organ biopsy in AL amyloidosis reflects failure to recognise the disease early in its course.

A simple receptor based on Congo-Red (CR) was prepared by complexation of CR into two equivalents of Cu (II) ([CR-(Cu)2]) and it has been designed for detection of sulfite and carbonate ions. This chemosensor exhibits high sensitivity for sulfite over other anions in aqueous buffer solution. It exhibits colorimetric \'naked eye\' and fluorometric responses to SO3(2-) which results from the addition of SO3(2)(-) to CR diazo moiety. Hereupon, CO3(2-) greatly limits the fluorescence of the resultant sulfite-receptor complex via a hydrogen bonding interaction ([CR-(Cu)2]-SO3). This system can be applied for selective detection of CO3(2-) in the presence of other anions. The detection limits of SO3(2-), calculated by the colorimetric and fluorometric methods, were found to be 0.07 and 0.09µmolL(-)(1), respectively. The sulfite-receptor complex also displayed the ability to detect up to 0.06µmolL(-)(1) CO3(2-). The fluorescence output mimicked \'INHIBIT\' logic gate function. The output was exhibited by the intramolecular charge transfer of the [CR-(Cu)2] probe, and was provided by chemical inputs (SO3(2-) and CO3(2-)).

OBJECTIVE: Morbidity and mortality due to preeclampsia in settings with limited resources often results from delayed diagnosis. The Congo Red Dot (CRD) test, a simple modality to assess the presence of misfolded proteins in urine, shows promise as a diagnostic and prognostic tool for preeclampsia. We propose an innovative mobile health (mHealth) solution that enables the quantification of the CRD test as a batch laboratory test, with minimal cost and equipment.
METHODS: A smartphone application that guides the user through seven easy steps, and that can be used successfully by non-specialized personnel, was developed. After image acquisition, a robust analysis runs on a smartphone, quantifying the CRD test response without the need for an internet connection or additional hardware. In the first stage, the basic image processing algorithms and supporting test standardizations were developed using urine samples from 218 patients. In the second stage, the standardized procedure was evaluated on 328 urine specimens from 273 women. In the third stage, the application was tested for robustness using four different operators and 94 altered samples.
RESULTS: In the first stage, the image processing chain was set up with high correlation to manual analysis (z-test P < 0.001). In the second stage, a high agreement between manual and automated processing was calculated (Lin\'s concordance coefficient ρc = 0.968). In the last stage, sources of error were identified and remedies were developed accordingly. Altered samples resulted in an acceptable concordance with the manual gold-standard (Lin\'s ρc = 0.914).
CONCLUSIONS: Combining smartphone-based image analysis with molecular-specific disease features represents a cost-effective application of mHealth that has the potential to fill gaps in access to health care solutions that are critical to reducing adverse events in resource-poor settings.